{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "1、导入必要的包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2、读取训练数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_data_path = r\"./data/train.csv\"\n",
    "df = pd.read_csv(train_data_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1、 单个特征分布、特征对结果的影响"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3、查看数据集top 5，包括数据集的特征种类和数量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>click</th>\n",
       "      <th>hour</th>\n",
       "      <th>C1</th>\n",
       "      <th>banner_pos</th>\n",
       "      <th>site_id</th>\n",
       "      <th>site_domain</th>\n",
       "      <th>site_category</th>\n",
       "      <th>app_id</th>\n",
       "      <th>app_domain</th>\n",
       "      <th>...</th>\n",
       "      <th>device_type</th>\n",
       "      <th>device_conn_type</th>\n",
       "      <th>C14</th>\n",
       "      <th>C15</th>\n",
       "      <th>C16</th>\n",
       "      <th>C17</th>\n",
       "      <th>C18</th>\n",
       "      <th>C19</th>\n",
       "      <th>C20</th>\n",
       "      <th>C21</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.000009e+18</td>\n",
       "      <td>0</td>\n",
       "      <td>14102100</td>\n",
       "      <td>1005</td>\n",
       "      <td>0</td>\n",
       "      <td>1fbe01fe</td>\n",
       "      <td>f3845767</td>\n",
       "      <td>28905ebd</td>\n",
       "      <td>ecad2386</td>\n",
       "      <td>7801e8d9</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>15706</td>\n",
       "      <td>320</td>\n",
       "      <td>50</td>\n",
       "      <td>1722</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>-1</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.000017e+19</td>\n",
       "      <td>0</td>\n",
       "      <td>14102100</td>\n",
       "      <td>1005</td>\n",
       "      <td>0</td>\n",
       "      <td>1fbe01fe</td>\n",
       "      <td>f3845767</td>\n",
       "      <td>28905ebd</td>\n",
       "      <td>ecad2386</td>\n",
       "      <td>7801e8d9</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>15704</td>\n",
       "      <td>320</td>\n",
       "      <td>50</td>\n",
       "      <td>1722</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>100084</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.000037e+19</td>\n",
       "      <td>0</td>\n",
       "      <td>14102100</td>\n",
       "      <td>1005</td>\n",
       "      <td>0</td>\n",
       "      <td>1fbe01fe</td>\n",
       "      <td>f3845767</td>\n",
       "      <td>28905ebd</td>\n",
       "      <td>ecad2386</td>\n",
       "      <td>7801e8d9</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>15704</td>\n",
       "      <td>320</td>\n",
       "      <td>50</td>\n",
       "      <td>1722</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>100084</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.000064e+19</td>\n",
       "      <td>0</td>\n",
       "      <td>14102100</td>\n",
       "      <td>1005</td>\n",
       "      <td>0</td>\n",
       "      <td>1fbe01fe</td>\n",
       "      <td>f3845767</td>\n",
       "      <td>28905ebd</td>\n",
       "      <td>ecad2386</td>\n",
       "      <td>7801e8d9</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>15706</td>\n",
       "      <td>320</td>\n",
       "      <td>50</td>\n",
       "      <td>1722</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>100084</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.000068e+19</td>\n",
       "      <td>0</td>\n",
       "      <td>14102100</td>\n",
       "      <td>1005</td>\n",
       "      <td>1</td>\n",
       "      <td>fe8cc448</td>\n",
       "      <td>9166c161</td>\n",
       "      <td>0569f928</td>\n",
       "      <td>ecad2386</td>\n",
       "      <td>7801e8d9</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>18993</td>\n",
       "      <td>320</td>\n",
       "      <td>50</td>\n",
       "      <td>2161</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>-1</td>\n",
       "      <td>157</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  click      hour    C1  banner_pos   site_id site_domain  \\\n",
       "0  1.000009e+18      0  14102100  1005           0  1fbe01fe    f3845767   \n",
       "1  1.000017e+19      0  14102100  1005           0  1fbe01fe    f3845767   \n",
       "2  1.000037e+19      0  14102100  1005           0  1fbe01fe    f3845767   \n",
       "3  1.000064e+19      0  14102100  1005           0  1fbe01fe    f3845767   \n",
       "4  1.000068e+19      0  14102100  1005           1  fe8cc448    9166c161   \n",
       "\n",
       "  site_category    app_id app_domain ...  device_type device_conn_type    C14  \\\n",
       "0      28905ebd  ecad2386   7801e8d9 ...            1                2  15706   \n",
       "1      28905ebd  ecad2386   7801e8d9 ...            1                0  15704   \n",
       "2      28905ebd  ecad2386   7801e8d9 ...            1                0  15704   \n",
       "3      28905ebd  ecad2386   7801e8d9 ...            1                0  15706   \n",
       "4      0569f928  ecad2386   7801e8d9 ...            1                0  18993   \n",
       "\n",
       "   C15  C16   C17  C18  C19     C20  C21  \n",
       "0  320   50  1722    0   35      -1   79  \n",
       "1  320   50  1722    0   35  100084   79  \n",
       "2  320   50  1722    0   35  100084   79  \n",
       "3  320   50  1722    0   35  100084   79  \n",
       "4  320   50  2161    0   35      -1  157  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4、查看特征的类型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 40428967 entries, 0 to 40428966\n",
      "Data columns (total 24 columns):\n",
      "id                  float64\n",
      "click               int64\n",
      "hour                int64\n",
      "C1                  int64\n",
      "banner_pos          int64\n",
      "site_id             object\n",
      "site_domain         object\n",
      "site_category       object\n",
      "app_id              object\n",
      "app_domain          object\n",
      "app_category        object\n",
      "device_id           object\n",
      "device_ip           object\n",
      "device_model        object\n",
      "device_type         int64\n",
      "device_conn_type    int64\n",
      "C14                 int64\n",
      "C15                 int64\n",
      "C16                 int64\n",
      "C17                 int64\n",
      "C18                 int64\n",
      "C19                 int64\n",
      "C20                 int64\n",
      "C21                 int64\n",
      "dtypes: float64(1), int64(14), object(9)\n",
      "memory usage: 7.2+ GB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5、查看匿名特征的分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>C1</th>\n",
       "      <th>C14</th>\n",
       "      <th>C15</th>\n",
       "      <th>C16</th>\n",
       "      <th>C17</th>\n",
       "      <th>C18</th>\n",
       "      <th>C19</th>\n",
       "      <th>C20</th>\n",
       "      <th>C21</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4.042897e+07</td>\n",
       "      <td>4.042897e+07</td>\n",
       "      <td>4.042897e+07</td>\n",
       "      <td>4.042897e+07</td>\n",
       "      <td>4.042897e+07</td>\n",
       "      <td>4.042897e+07</td>\n",
       "      <td>4.042897e+07</td>\n",
       "      <td>4.042897e+07</td>\n",
       "      <td>4.042897e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.004968e+03</td>\n",
       "      <td>1.884181e+04</td>\n",
       "      <td>3.188831e+02</td>\n",
       "      <td>6.010201e+01</td>\n",
       "      <td>2.112601e+03</td>\n",
       "      <td>1.432499e+00</td>\n",
       "      <td>2.271444e+02</td>\n",
       "      <td>5.321685e+04</td>\n",
       "      <td>8.338229e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.094586e+00</td>\n",
       "      <td>4.959457e+03</td>\n",
       "      <td>2.127250e+01</td>\n",
       "      <td>4.729538e+01</td>\n",
       "      <td>6.094124e+02</td>\n",
       "      <td>1.326227e+00</td>\n",
       "      <td>3.510221e+02</td>\n",
       "      <td>4.995682e+04</td>\n",
       "      <td>7.028996e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.001000e+03</td>\n",
       "      <td>3.750000e+02</td>\n",
       "      <td>1.200000e+02</td>\n",
       "      <td>2.000000e+01</td>\n",
       "      <td>1.120000e+02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.300000e+01</td>\n",
       "      <td>-1.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.005000e+03</td>\n",
       "      <td>1.692000e+04</td>\n",
       "      <td>3.200000e+02</td>\n",
       "      <td>5.000000e+01</td>\n",
       "      <td>1.863000e+03</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.500000e+01</td>\n",
       "      <td>-1.000000e+00</td>\n",
       "      <td>2.300000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.005000e+03</td>\n",
       "      <td>2.034600e+04</td>\n",
       "      <td>3.200000e+02</td>\n",
       "      <td>5.000000e+01</td>\n",
       "      <td>2.323000e+03</td>\n",
       "      <td>2.000000e+00</td>\n",
       "      <td>3.900000e+01</td>\n",
       "      <td>1.000480e+05</td>\n",
       "      <td>6.100000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.005000e+03</td>\n",
       "      <td>2.189400e+04</td>\n",
       "      <td>3.200000e+02</td>\n",
       "      <td>5.000000e+01</td>\n",
       "      <td>2.526000e+03</td>\n",
       "      <td>3.000000e+00</td>\n",
       "      <td>1.710000e+02</td>\n",
       "      <td>1.000930e+05</td>\n",
       "      <td>1.010000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.012000e+03</td>\n",
       "      <td>2.405200e+04</td>\n",
       "      <td>1.024000e+03</td>\n",
       "      <td>1.024000e+03</td>\n",
       "      <td>2.758000e+03</td>\n",
       "      <td>3.000000e+00</td>\n",
       "      <td>1.959000e+03</td>\n",
       "      <td>1.002480e+05</td>\n",
       "      <td>2.550000e+02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 C1           C14           C15           C16           C17  \\\n",
       "count  4.042897e+07  4.042897e+07  4.042897e+07  4.042897e+07  4.042897e+07   \n",
       "mean   1.004968e+03  1.884181e+04  3.188831e+02  6.010201e+01  2.112601e+03   \n",
       "std    1.094586e+00  4.959457e+03  2.127250e+01  4.729538e+01  6.094124e+02   \n",
       "min    1.001000e+03  3.750000e+02  1.200000e+02  2.000000e+01  1.120000e+02   \n",
       "25%    1.005000e+03  1.692000e+04  3.200000e+02  5.000000e+01  1.863000e+03   \n",
       "50%    1.005000e+03  2.034600e+04  3.200000e+02  5.000000e+01  2.323000e+03   \n",
       "75%    1.005000e+03  2.189400e+04  3.200000e+02  5.000000e+01  2.526000e+03   \n",
       "max    1.012000e+03  2.405200e+04  1.024000e+03  1.024000e+03  2.758000e+03   \n",
       "\n",
       "                C18           C19           C20           C21  \n",
       "count  4.042897e+07  4.042897e+07  4.042897e+07  4.042897e+07  \n",
       "mean   1.432499e+00  2.271444e+02  5.321685e+04  8.338229e+01  \n",
       "std    1.326227e+00  3.510221e+02  4.995682e+04  7.028996e+01  \n",
       "min    0.000000e+00  3.300000e+01 -1.000000e+00  1.000000e+00  \n",
       "25%    0.000000e+00  3.500000e+01 -1.000000e+00  2.300000e+01  \n",
       "50%    2.000000e+00  3.900000e+01  1.000480e+05  6.100000e+01  \n",
       "75%    3.000000e+00  1.710000e+02  1.000930e+05  1.010000e+02  \n",
       "max    3.000000e+00  1.959000e+03  1.002480e+05  2.550000e+02  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['C1', 'C14', 'C15', 'C16', 'C17', 'C18', 'C19', 'C20', 'C21']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False    33563901\n",
      "True      6865066\n",
      "Name: click, dtype: int64\n",
      "点击概率为 0.16980562476404604\n"
     ]
    }
   ],
   "source": [
    "#点击率统计\n",
    "P_A=df['click'].value_counts()[1]/df['click'].value_counts().sum()\n",
    "print(df['click'].value_counts())\n",
    "print('点击概率为',P_A)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "hour属性的取值和次数\n",
      "                       特征分布       P_C     P_C|A     P_A|C     概率提升比%\n",
      "2014-10-22 09:00:00  447783  0.011076  0.009091  0.139376 -17.920537\n",
      "2014-10-22 10:00:00  438270  0.010840  0.008913  0.139613 -17.780952\n",
      "2014-10-28 13:00:00  432308  0.010693  0.008606  0.136662 -19.518670\n",
      "2014-10-22 12:00:00  408650  0.010108  0.008174  0.137323 -19.129362\n",
      "2014-10-28 14:00:00  387453  0.009584  0.008243  0.146051 -13.989149\n",
      "2014-10-22 11:00:00  386757  0.009566  0.007606  0.135015 -20.488494\n",
      "2014-10-30 04:00:00  347806  0.008603  0.005387  0.106321 -37.386783\n",
      "2014-10-28 09:00:00  328576  0.008127  0.005920  0.123694 -27.155319\n",
      "2014-10-22 13:00:00  323480  0.008001  0.006291  0.133520 -21.369008\n",
      "2014-10-22 08:00:00  322803  0.007984  0.006772  0.144010 -15.191011\n",
      "2014-10-28 08:00:00  291763  0.007217  0.005523  0.129951 -23.470518\n",
      "2014-10-22 06:00:00  288819  0.007144  0.006734  0.160055  -5.742074\n",
      "2014-10-22 05:00:00  286697  0.007091  0.006106  0.146221 -13.889440\n",
      "2014-10-28 16:00:00  283491  0.007012  0.006854  0.165984  -2.250526\n",
      "2014-10-28 15:00:00  282315  0.006983  0.006875  0.167179  -1.547133\n",
      "2014-10-28 17:00:00  280835  0.006946  0.006299  0.153991  -9.313500\n",
      "2014-10-21 05:00:00  273500  0.006765  0.005930  0.148845 -12.344125\n",
      "2014-10-23 04:00:00  273173  0.006757  0.006854  0.172257   1.443719\n",
      "2014-10-28 12:00:00  272124  0.006731  0.006505  0.164116  -3.350458\n",
      "2014-10-21 04:00:00  264711  0.006548  0.005830  0.151206 -10.953238\n",
      "2014-10-24 17:00:00  262579  0.006495  0.006039  0.157876  -7.025285\n",
      "2014-10-30 14:00:00  259187  0.006411  0.006381  0.169013  -0.466721\n",
      "2014-10-28 10:00:00  258656  0.006398  0.005347  0.141926 -16.418578\n",
      "2014-10-28 11:00:00  257891  0.006379  0.005734  0.152650 -10.103235\n",
      "2014-10-24 16:00:00  252154  0.006237  0.006000  0.163357  -3.797933\n",
      "2014-10-30 13:00:00  250441  0.006195  0.006120  0.167764  -1.202293\n",
      "2014-10-30 12:00:00  249022  0.006159  0.005961  0.164343  -3.217040\n",
      "2014-10-23 15:00:00  246297  0.006092  0.006038  0.168289  -0.893335\n",
      "2014-10-30 05:00:00  244765  0.006054  0.004815  0.135040 -20.473935\n",
      "2014-10-25 14:00:00  242500  0.005998  0.006637  0.187893  10.651684\n",
      "...                     ...       ...       ...       ...        ...\n",
      "2014-10-21 21:00:00   89501  0.002214  0.002215  0.169886   0.047552\n",
      "2014-10-23 00:00:00   89341  0.002210  0.002470  0.189767  11.755601\n",
      "2014-10-26 22:00:00   88869  0.002198  0.002079  0.160607  -5.417040\n",
      "2014-10-21 22:00:00   88436  0.002187  0.002314  0.179599   5.767289\n",
      "2014-10-30 00:00:00   87333  0.002160  0.002572  0.202215  19.085874\n",
      "2014-10-27 23:00:00   87207  0.002157  0.002266  0.178369   5.042874\n",
      "2014-10-27 02:00:00   85828  0.002123  0.002295  0.183576   8.109761\n",
      "2014-10-30 23:00:00   83608  0.002068  0.002056  0.168836  -0.571304\n",
      "2014-10-28 00:00:00   82520  0.002041  0.002247  0.186949  10.095657\n",
      "2014-10-24 00:00:00   82137  0.002032  0.002149  0.179615   5.776559\n",
      "2014-10-26 21:00:00   82130  0.002031  0.001846  0.154304  -9.128951\n",
      "2014-10-26 01:00:00   80863  0.002000  0.002209  0.187577  10.465433\n",
      "2014-10-25 01:00:00   80637  0.001995  0.002202  0.187507  10.424479\n",
      "2014-10-22 00:00:00   78006  0.001929  0.002088  0.183755   8.214964\n",
      "2014-10-25 04:00:00   76816  0.001900  0.002061  0.184193   8.473084\n",
      "2014-10-26 23:00:00   76770  0.001899  0.001986  0.177556   4.564461\n",
      "2014-10-25 23:00:00   76506  0.001892  0.002065  0.185253   9.097354\n",
      "2014-10-27 01:00:00   75382  0.001865  0.002315  0.210820  24.153460\n",
      "2014-10-21 23:00:00   73940  0.001829  0.002027  0.188193  10.828560\n",
      "2014-10-25 00:00:00   73446  0.001817  0.001975  0.184598   8.711480\n",
      "2014-10-26 00:00:00   72185  0.001785  0.001916  0.182254   7.330915\n",
      "2014-10-25 03:00:00   67443  0.001668  0.001387  0.141216 -16.836945\n",
      "2014-10-27 00:00:00   62254  0.001540  0.001646  0.181563   6.923802\n",
      "2014-10-25 06:00:00   51726  0.001279  0.001224  0.162413  -4.353294\n",
      "2014-10-25 02:00:00   38400  0.000950  0.000647  0.115703 -31.861430\n",
      "2014-10-24 19:00:00   34163  0.000845  0.000595  0.119515 -29.616427\n",
      "2014-10-24 23:00:00   25622  0.000634  0.000528  0.141597 -16.612265\n",
      "2014-10-24 20:00:00   23124  0.000572  0.000464  0.137649 -18.937199\n",
      "2014-10-24 21:00:00   20367  0.000504  0.000389  0.131045 -22.826279\n",
      "2014-10-24 22:00:00   14876  0.000368  0.000331  0.152796 -10.016850\n",
      "\n",
      "[240 rows x 5 columns]\n",
      "\n",
      "C1属性的取值和次数\n",
      "          特征分布       P_C     P_C|A     P_A|C     概率提升比%\n",
      "1005  37140632  0.918664  0.916095  0.169331  -0.279580\n",
      "1002   2220812  0.054931  0.068171  0.210731  24.101590\n",
      "1010    903457  0.022347  0.012531  0.095215 -43.926841\n",
      "1012    113512  0.002808  0.002852  0.172493   1.582487\n",
      "1007     35304  0.000873  0.000203  0.039429 -76.779945\n",
      "1001      9463  0.000234  0.000046  0.033393 -80.334447\n",
      "1008      5787  0.000143  0.000103  0.121652 -28.358098\n",
      "\n",
      "banner_pos属性的取值和次数\n",
      "       特征分布       P_C     P_C|A     P_A|C     概率提升比%\n",
      "0  29109590  0.720018  0.696556  0.164272  -3.258588\n",
      "1  11247282  0.278199  0.300822  0.183614   8.132163\n",
      "7     43577  0.001078  0.002032  0.320100  88.509688\n",
      "2     13001  0.000322  0.000226  0.119222 -29.789370\n",
      "4      7704  0.000191  0.000208  0.185358   9.159079\n",
      "5      5778  0.000143  0.000102  0.121495 -28.450352\n",
      "3      2035  0.000050  0.000054  0.182801   7.653079\n",
      "\n",
      "site_id属性的取值和次数\n",
      "              特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "85f751fd  14596137  3.610317e-01  2.526424e-01  0.118826  -30.022082\n",
      "1fbe01fe   6486150  1.604332e-01  1.942828e-01  0.205633   21.098825\n",
      "e151e245   2637747  6.524399e-02  1.138559e-01  0.296324   74.507822\n",
      "d9750ee7    963745  2.383798e-02  3.932446e-02  0.280121   64.965548\n",
      "5b08c53b    913325  2.259086e-02  6.215672e-02  0.467205  175.141058\n",
      "5b4d2eda    771360  1.907939e-02  1.460831e-02  0.130013  -23.434089\n",
      "856e6d3f    765891  1.894411e-02  4.769947e-03  0.042755  -74.820957\n",
      "a7853007    461311  1.141041e-02  6.873641e-03  0.102291  -39.759899\n",
      "b7e9786d    369099  9.129568e-03  3.979423e-03  0.074015  -56.411707\n",
      "5ee41ff2    349008  8.632622e-03  1.683961e-02  0.331239   95.069407\n",
      "6399eda6    343703  8.501404e-03  5.303809e-03  0.105937  -37.612553\n",
      "5bcf81a2    340050  8.411048e-03  5.722305e-03  0.115524  -31.966807\n",
      "6256f5b4    315840  7.812220e-03  8.098393e-03  0.176026    3.663136\n",
      "57ef2c87    310760  7.686568e-03  5.496233e-03  0.121418  -28.495621\n",
      "17caea14    278322  6.884222e-03  9.864435e-03  0.243315   43.290481\n",
      "0a742914    269725  6.671578e-03  1.054003e-02  0.268266   57.984064\n",
      "83a0ad1a    268735  6.647090e-03  3.331505e-03  0.085106  -49.880255\n",
      "57fe1b20    264952  6.553519e-03  9.513674e-03  0.246505   45.168941\n",
      "e4d8dd7b    259347  6.414881e-03  4.514159e-03  0.119492  -29.629883\n",
      "e8f79e60    259289  6.413446e-03  9.644044e-03  0.255341   50.372266\n",
      "d6137915    233281  5.770145e-03  7.954767e-03  0.234095   37.860782\n",
      "12fb4121    192890  4.771084e-03  5.140519e-04  0.018295  -89.225680\n",
      "6c5b482c    191220  4.729777e-03  1.170652e-02  0.420280  147.506704\n",
      "93eaba74    185620  4.591262e-03  1.255458e-02  0.464325  173.444985\n",
      "e5c60a05    179039  4.428483e-03  1.221110e-03  0.046822  -72.426001\n",
      "9a977531    173840  4.299887e-03  2.322920e-03  0.091734  -45.977185\n",
      "bb4524e7    168279  4.162337e-03  1.653298e-03  0.067448  -60.279577\n",
      "5114c672    165486  4.093253e-03  1.656211e-03  0.068707  -59.538020\n",
      "e3c09f3a    160321  3.965498e-03  7.114280e-04  0.030464  -82.059557\n",
      "4bf5bbe2    148511  3.673381e-03  1.389091e-02  0.642121  278.150480\n",
      "...            ...           ...           ...       ...         ...\n",
      "05ef938b         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "2de2ca76         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "a9caff76         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "4e91d0c7         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "392628ab         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "7b8dd9d1         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "a4f6ee5e         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "2caeb3df         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "c3fea8f2         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "bfb9afb4         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "f4ae4c6d         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "2bd62959         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "96fcf467         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "e92d8be1         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "b7aa40c1         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "a1538e7e         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "dead5491         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "356d4fe6         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "2f2f9872         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "4a64ae04         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "f8993cdc         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "f56bdf01         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "c7722f88         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "ecd5c70e         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "ca7b62ba         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "ad2b4369         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "b2f3f1b5         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "5ba2c590         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "f8f45980         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "e51df23f         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "\n",
      "[4737 rows x 5 columns]\n",
      "\n",
      "site_domain属性的取值和次数\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "c4e18dd6  15131739  3.742796e-01  2.705616e-01  0.122750  -27.711385\n",
      "f3845767   6486150  1.604332e-01  1.942828e-01  0.205633   21.098825\n",
      "7e091613   3325008  8.224321e-02  1.251321e-01  0.258357   52.148831\n",
      "7687a86e   1290165  3.191190e-02  8.641781e-02  0.459836  170.801252\n",
      "98572c79    996816  2.465598e-02  3.983880e-02  0.274370   61.578624\n",
      "16a36ef3    855686  2.116517e-02  1.773195e-02  0.142261  -16.221093\n",
      "58a89a43    765891  1.894411e-02  4.769947e-03  0.042755  -74.820957\n",
      "9d54950b    375891  9.297566e-03  6.151580e-03  0.112349  -33.836668\n",
      "b12b9f85    373925  9.248938e-03  4.077310e-03  0.074857  -55.915914\n",
      "17d996e6    353600  8.746204e-03  1.693167e-02  0.328725   93.588727\n",
      "968765cd    343703  8.501404e-03  5.303809e-03  0.105937  -37.612553\n",
      "28f93029    315842  7.812270e-03  8.098684e-03  0.176031    3.666209\n",
      "bd6d812f    310760  7.686568e-03  5.496233e-03  0.121418  -28.495621\n",
      "d262cf1e    289921  7.171121e-03  9.326931e-04  0.022085  -86.993760\n",
      "0dde25ec    278322  6.884222e-03  9.864435e-03  0.243315   43.290481\n",
      "510bd839    269725  6.671578e-03  1.054003e-02  0.268266   57.984064\n",
      "5c9ae867    268735  6.647090e-03  3.331505e-03  0.085106  -49.880255\n",
      "5b626596    265874  6.576324e-03  9.518627e-03  0.245778   44.740833\n",
      "a17bde68    259347  6.414881e-03  4.514159e-03  0.119492  -29.629883\n",
      "c4342784    259289  6.413446e-03  9.644044e-03  0.255341   50.372266\n",
      "6b59f079    241035  5.961938e-03  9.216226e-04  0.026249  -84.541560\n",
      "bb1ef334    233282  5.770170e-03  7.954767e-03  0.234094   37.860191\n",
      "7256c623    219219  5.422325e-03  1.482433e-03  0.046424  -72.660567\n",
      "a434fa42    205311  5.078314e-03  2.899025e-03  0.096936  -42.913630\n",
      "d733bbc3    168280  4.162362e-03  1.653298e-03  0.067447  -60.279813\n",
      "3f2f3819    165486  4.093253e-03  1.656211e-03  0.068707  -59.538020\n",
      "6b560cc1    148511  3.673381e-03  1.389091e-02  0.642121  278.150480\n",
      "c1aa3c04    128890  3.188061e-03  7.577495e-04  0.040360  -76.231649\n",
      "27e3c518    128180  3.170499e-03  1.512440e-03  0.081003  -52.296470\n",
      "e2a5dc06    117606  2.908954e-03  1.496854e-03  0.087376  -48.543227\n",
      "...            ...           ...           ...       ...         ...\n",
      "af3cb2bf         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "ec24f70e         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "05953de0         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
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      "8bca33c1         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "fd4e4b4c         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "4fcec3df         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "eac4b09a         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "60c05a1d         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "5c6f8a85         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "7ae0fe7a         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
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      "c70459ec         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "2baf57b2         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "dc5ed23b         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "2bad629e         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "70bc562c         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "473e0b54         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "1c9aec74         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "8ad2ac4d         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "1dc77f74         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "adacaa75         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
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      "a7ee4a45         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "7b20d69f         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "12c802b1         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "372c2fae         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "c3c1a329         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "\n",
      "[7745 rows x 5 columns]\n",
      "\n",
      "site_category属性的取值和次数\n",
      "              特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "50e219e0  16537234  4.090442e-01  3.097348e-01  0.128580  -24.278396\n",
      "f028772b  12657073  3.130694e-01  3.310879e-01  0.179579    5.755415\n",
      "28905ebd   7377208  1.824733e-01  2.235375e-01  0.208019   22.504232\n",
      "3e814130   3050306  7.544853e-02  1.257446e-01  0.283003   66.662768\n",
      "f66779e6    252451  6.244310e-03  1.459418e-03  0.039687  -76.628036\n",
      "75fa27f6    160985  3.981922e-03  2.609589e-03  0.111284  -34.464091\n",
      "335d28a8    136463  3.375377e-03  1.861453e-03  0.093644  -44.851985\n",
      "76b2941d    104754  2.591063e-03  4.617581e-04  0.030261  -82.178815\n",
      "c0dd3be3     42090  1.041085e-03  6.866649e-04  0.111998  -34.043351\n",
      "72722551     28216  6.979154e-04  2.368513e-04  0.057627  -66.063033\n",
      "dedf689d     24500  6.060011e-04  1.834360e-03  0.514000  202.699042\n",
      "70fb0e29     24224  5.991743e-04  4.804032e-04  0.136146  -19.822461\n",
      "0569f928     17106  4.231125e-04  1.344488e-04  0.053958  -68.223858\n",
      "8fd0aea4      7482  1.850653e-04  1.616882e-05  0.014836  -91.263184\n",
      "a818d37a      3230  7.989321e-05  1.893645e-06  0.004025  -97.629779\n",
      "42a36e14      2515  6.220787e-05  8.463138e-05  0.231014   36.046092\n",
      "e787de0e      1209  2.990430e-05  1.296419e-05  0.073615  -56.647751\n",
      "bcf865d9      1045  2.584780e-05  6.991921e-06  0.045933  -72.949651\n",
      "5378d028       483  1.194688e-05  6.700591e-06  0.095238  -43.913463\n",
      "9ccfa2ea       318  7.865647e-06  5.826601e-07  0.012579  -92.592344\n",
      "c706e647        28  6.925727e-07  0.000000e+00  0.000000 -100.000000\n",
      "da34532e        23  5.688990e-07  0.000000e+00  0.000000 -100.000000\n",
      "74073276        14  3.462864e-07  2.913300e-07  0.142857  -15.870194\n",
      "110ab22d         6  1.484084e-07  0.000000e+00  0.000000 -100.000000\n",
      "6432c423         2  4.946948e-08  0.000000e+00  0.000000 -100.000000\n",
      "a72a0145         2  4.946948e-08  0.000000e+00  0.000000 -100.000000\n",
      "\n",
      "app_id属性的取值和次数\n",
      "              特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "ecad2386  25832830  6.389683e-01  7.473576e-01  0.198610   16.963160\n",
      "92f5800b   1555283  3.846952e-02  4.371990e-03  0.019298  -88.635185\n",
      "e2fcccd2   1129016  2.792592e-02  3.200100e-02  0.194584   14.592487\n",
      "febd1138    759098  1.877609e-02  5.330903e-03  0.048211  -71.608027\n",
      "9c13b419    757812  1.874428e-02  3.370499e-02  0.305336   79.814788\n",
      "7358e05e    615635  1.522757e-02  1.679678e-02  0.187304   10.305042\n",
      "a5184c22    491457  1.215606e-02  1.770019e-02  0.247251   45.607970\n",
      "d36838b1    457572  1.131792e-02  4.733676e-03  0.071021  -58.175404\n",
      "685d1c4c    408515  1.010451e-02  4.523627e-03  0.076019  -55.231612\n",
      "54c5d545    397693  9.836833e-03  7.197309e-03  0.124242  -26.833070\n",
      "03528b27    322121  7.967579e-03  6.446551e-03  0.137389  -19.090215\n",
      "f0d41ff1    294244  7.278049e-03  2.572007e-03  0.060008  -64.660758\n",
      "e9739828    284750  7.043217e-03  1.163864e-03  0.028060  -83.475399\n",
      "e2a1ca37    281215  6.955780e-03  5.714585e-03  0.139505  -17.844087\n",
      "51cedd4e    239107  5.914250e-03  1.816297e-03  0.052148  -69.289473\n",
      "66f5e02e    226077  5.591956e-03  7.467226e-03  0.226750   33.535140\n",
      "03a08c3f    218767  5.411145e-03  1.825474e-03  0.057285  -66.264550\n",
      "98fed791    218766  5.411120e-03  4.366309e-03  0.137019  -19.308592\n",
      "73206397    200058  4.948383e-03  8.569473e-04  0.029406  -82.682274\n",
      "f53417e1    199043  4.923277e-03  2.010906e-03  0.069357  -59.155138\n",
      "e96773f0    178745  4.421211e-03  1.880098e-03  0.072209  -57.475488\n",
      "ce183bbd    148257  3.667098e-03  1.245436e-03  0.057670  -66.037564\n",
      "be7c618d    119975  2.967550e-03  2.603471e-03  0.148973  -12.268688\n",
      "1dc72b4d    105288  2.604271e-03  1.820084e-03  0.118674  -30.111566\n",
      "f888bf4c    104413  2.582628e-03  8.725335e-04  0.057368  -66.215291\n",
      "396df801     98066  2.425637e-03  2.688102e-03  0.188179   10.820469\n",
      "3c4b944d     89039  2.202357e-03  2.120591e-03  0.163501   -3.712620\n",
      "39947756     86799  2.146951e-03  5.402716e-04  0.042731  -74.835400\n",
      "cf0327f9     86477  2.138986e-03  1.090740e-03  0.086589  -49.006696\n",
      "3f2a6cbb     83356  2.061789e-03  2.761809e-04  0.022746  -86.604794\n",
      "...            ...           ...           ...       ...         ...\n",
      "5507e79b         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "090d37ad         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "611a4fee         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "45d1fef3         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "0a7c4dee         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "acc1cf97         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "6eb0d76e         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "9e1296f2         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "939a290e         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "9d8980d6         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "0ebec02b         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "b06683cc         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "aeeaf63e         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "e0366e95         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "e7fa2a2b         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "0cc2e0a2         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "5497f0d0         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "83211704         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "54bf3a17         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "a45dc958         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "b0af65f3         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "4966987a         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "87397e22         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "8b0ee20f         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "7f3710e2         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "040aced3         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "a48ecc3a         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "75da5998         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "b622e379         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "6e99829f         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "\n",
      "[8552 rows x 5 columns]\n",
      "\n",
      "app_domain属性的取值和次数\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "7801e8d9  27237087  6.737023e-01  7.731741e-01  0.194877   14.764948\n",
      "2347f47a   5240885  1.296319e-01  1.054380e-01  0.138114  -18.663538\n",
      "ae637522   1881838  4.654677e-02  6.518947e-03  0.023782  -85.994847\n",
      "5c5a694b   1129228  2.793116e-02  3.200246e-02  0.194557   14.576188\n",
      "82e27996    759125  1.877676e-02  5.331049e-03  0.048211  -71.608261\n",
      "d9b5648e    713924  1.765872e-02  1.154759e-02  0.111041  -34.606859\n",
      "0e8616ad    660510  1.633754e-02  6.812170e-03  0.070803  -58.303581\n",
      "b9528b13    646193  1.598342e-02  1.702576e-02  0.180879    6.521440\n",
      "b8d325c3    534000  1.320835e-02  1.807310e-02  0.232346   36.830828\n",
      "aefc06bd    298769  7.389974e-03  3.112716e-03  0.071523  -57.879202\n",
      "df32afa9    291502  7.210226e-03  1.184111e-03  0.027887  -83.577340\n",
      "33da2e74    259530  6.419407e-03  4.534989e-03  0.119959  -29.355016\n",
      "6f7ca2ba    226100  5.592525e-03  7.467226e-03  0.226727   33.521556\n",
      "5b9c592b    104413  2.582628e-03  8.725335e-04  0.057368  -66.215291\n",
      "885c7f3f     68310  1.689630e-03  1.673691e-03  0.168204   -0.943342\n",
      "5c620f04     60268  1.490713e-03  2.400560e-04  0.027345  -83.896571\n",
      "45a51db4     56138  1.388559e-03  1.644704e-03  0.201129   18.446818\n",
      "b5f3b24a     48199  1.192190e-03  2.785115e-04  0.039669  -76.638658\n",
      "813f3323     25338  6.267289e-04  4.246135e-04  0.115045  -32.249243\n",
      "0654b444     23298  5.762700e-04  6.815666e-04  0.200833   18.272107\n",
      "ad63ec9b     17624  4.359251e-04  1.009459e-04  0.039321  -76.843300\n",
      "c6824def     14288  3.534100e-04  4.792379e-05  0.023026  -86.439604\n",
      "15ec7f39     13031  3.223184e-04  2.811335e-05  0.014811  -91.277771\n",
      "a8b0bf20     13009  3.217742e-04  8.739901e-05  0.046122  -72.838405\n",
      "99b4c806     10041  2.483615e-04  9.372088e-04  0.640773  277.356658\n",
      "828da833      8268  2.045068e-04  2.651103e-05  0.022013  -87.036602\n",
      "43cf4f06      7199  1.780654e-04  3.510527e-05  0.033477  -80.285181\n",
      "448ca2e3      6877  1.701008e-04  2.243241e-05  0.022393  -86.812283\n",
      "f2f777fb      6532  1.615673e-04  5.447872e-05  0.057257  -66.281103\n",
      "47464e95      4761  1.177621e-04  4.952611e-05  0.071414  -57.943932\n",
      "...            ...           ...           ...       ...         ...\n",
      "7c17d732         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "70146488         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "b1ab9955         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "505949a0         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
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      "1c73b8ac         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "7366e108         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "1dc4224a         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "93f9275a         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "11c6546c         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "a67cb0c5         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
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      "741bb270         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "0b793b58         1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "c9f545d5         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "139260e0         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "8bba499a         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "e559a22e         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "76a8fa7c         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "d22b6d64         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "116fd53f         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "bd6843b4         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "790dd3cc         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "31d17fc8         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "d80e8488         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "8e8ca1d0         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "\n",
      "[559 rows x 5 columns]\n",
      "\n",
      "app_category属性的取值和次数\n",
      "              特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "07d7df22  26165592  6.471991e-01  7.590345e-01  0.199148   17.279904\n",
      "0f2161f8   9561058  2.364903e-01  1.505768e-01  0.108118  -36.328527\n",
      "cef3e649   1731545  4.282932e-02  2.351762e-02  0.093240  -45.089905\n",
      "8ded1f7a   1467257  3.629222e-02  1.923084e-02  0.089978  -47.011118\n",
      "f95efa07   1141673  2.823899e-02  4.117426e-02  0.247588   45.806437\n",
      "d1327cf5    123233  3.048136e-03  2.213671e-03  0.123319  -27.376233\n",
      "09481d60     54886  1.357591e-03  1.240775e-03  0.155194   -8.604675\n",
      "dc97ec06     54644  1.351605e-03  1.245727e-03  0.156504   -7.833491\n",
      "75d80bbe     40108  9.920610e-04  5.606647e-04  0.095966  -43.484857\n",
      "fc6fa53d     23663  5.852982e-04  1.672234e-04  0.048515  -71.429357\n",
      "4ce2e9fc     20762  5.135427e-04  3.743591e-04  0.123784  -27.102629\n",
      "879c24eb     12785  3.162337e-04  1.950455e-04  0.104732  -38.322356\n",
      "a3c42688     11121  2.750750e-04  7.647414e-05  0.047208  -72.198810\n",
      "4681bb9d      6291  1.556063e-04  1.322638e-04  0.144333  -15.000946\n",
      "0f9a328c      5584  1.381188e-04  1.262916e-04  0.155265   -8.563074\n",
      "a86a3e89      2497  6.176265e-05  4.734113e-05  0.130156  -23.349896\n",
      "2281a340      2243  5.548002e-05  4.369951e-06  0.013375  -92.123380\n",
      "8df2e842      1679  4.152963e-05  6.350995e-05  0.259678   52.926842\n",
      "79f0b860       605  1.496452e-05  5.098276e-06  0.057851  -65.930905\n",
      "0bfbc358       425  1.051226e-05  1.019655e-06  0.016471  -90.300328\n",
      "a7fd01ec       362  8.953976e-06  8.011576e-06  0.151934  -10.524930\n",
      "7113d72a       304  7.519361e-06  4.369951e-07  0.009868  -94.188402\n",
      "2fc4f2aa       234  5.787929e-06  5.826601e-07  0.017094  -89.933186\n",
      "18b1e0be       212  5.243765e-06  2.184975e-06  0.070755  -58.331936\n",
      "5326cf99       133  3.289720e-06  1.456650e-07  0.007519  -95.572115\n",
      "0d82db25        25  6.183685e-07  5.826601e-07  0.160000   -5.774617\n",
      "4b7ade46        16  3.957558e-07  0.000000e+00  0.000000 -100.000000\n",
      "bf8ac856         9  2.226127e-07  0.000000e+00  0.000000 -100.000000\n",
      "bd41f328         6  1.484084e-07  0.000000e+00  0.000000 -100.000000\n",
      "71af18ce         5  1.236737e-07  1.456650e-07  0.200000   17.781729\n",
      "86c1a5a3         3  7.420422e-08  0.000000e+00  0.000000 -100.000000\n",
      "ef03ae90         2  4.946948e-08  0.000000e+00  0.000000 -100.000000\n",
      "6fea3693         2  4.946948e-08  0.000000e+00  0.000000 -100.000000\n",
      "52de74cf         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "f395a87f         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "cba0e20d         1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "\n",
      "device_id属性的取值和次数\n",
      "              特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "a99f214a  33358308  8.251091e-01  8.462286e-01  0.174152    2.559599\n",
      "0f7c61dc     21356  5.282351e-04  2.358317e-03  0.758101  346.452094\n",
      "c357dbff     19667  4.864581e-04  1.816297e-03  0.634006  273.371733\n",
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      "b09da1c4      3655  9.040548e-05  6.977355e-05  0.131053  -22.821549\n",
      "3cdb4052      3069  7.591092e-05  3.526550e-04  0.788856  364.564296\n",
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      "73b81e30      1182  2.923646e-05  9.118630e-05  0.529611  211.892395\n",
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      "...            ...           ...           ...       ...         ...\n",
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      "\n",
      "[2686408 rows x 5 columns]\n",
      "\n",
      "device_ip属性的取值和次数\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "6b9769f2  208701  5.162165e-03  6.698697e-03  0.220349   29.765271\n",
      "431b3174  135322  3.347155e-03  3.839147e-03  0.194765   14.698838\n",
      "2f323f36   88499  2.189000e-03  1.272238e-03  0.098690  -41.880382\n",
      "af9205f9   87844  2.172799e-03  1.229121e-03  0.096057  -43.431411\n",
      "930ec31d   86996  2.151823e-03  1.190229e-03  0.093924  -44.687428\n",
      "af62faf4   85802  2.122290e-03  1.175225e-03  0.094030  -44.624660\n",
      "009a7861   85382  2.111902e-03  1.201445e-03  0.096601  -43.110744\n",
      "285aa37d   85313  2.110195e-03  1.186442e-03  0.095472  -43.775733\n",
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      "d90a7774   82980  2.052489e-03  1.122349e-03  0.092854  -45.317654\n",
      "c6563308   71290  1.763340e-03  2.211195e-03  0.212933   25.398137\n",
      "57cd4006   70449  1.742538e-03  2.205660e-03  0.214936   26.577448\n",
      "75bb1b58   70262  1.737912e-03  2.190948e-03  0.214070   26.067788\n",
      "1cf29716   70028  1.732124e-03  2.197940e-03  0.215471   26.892707\n",
      "ddd2926e   69816  1.726881e-03  2.173176e-03  0.213690   25.844048\n",
      "0489ce3f   69756  1.725397e-03  2.184975e-03  0.215035   26.636127\n",
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      "95b2935e   29576  7.315547e-04  8.180548e-04  0.189884   11.824146\n",
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      "ff1c4f79   29353  7.260388e-04  8.141218e-04  0.190406   12.131993\n",
      "...          ...           ...           ...       ...         ...\n",
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      "\n",
      "[6729486 rows x 5 columns]\n",
      "\n",
      "device_model属性的取值和次数\n",
      "             特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "8a4875bd  2455470  6.073541e-02  4.943230e-02  0.138204  -18.610416\n",
      "1f0bc64f  1424546  3.523578e-02  4.658338e-02  0.224491   32.204791\n",
      "d787e91b  1405169  3.475649e-02  4.582243e-02  0.223869   31.838482\n",
      "76dc4769   767961  1.899532e-02  2.117766e-02  0.189314   11.488828\n",
      "be6db1d7   742913  1.837576e-02  2.038975e-02  0.188416   10.960052\n",
      "a0f5f879   652751  1.614563e-02  1.583437e-02  0.166532   -1.927802\n",
      "4ea23a13   645153  1.595769e-02  1.990148e-02  0.211771   24.714050\n",
      "7abbbd5c   636673  1.574794e-02  1.600087e-02  0.172533    1.606080\n",
      "ecb851b2   613048  1.516358e-02  1.616955e-02  0.181071    6.634071\n",
      "d4897fef   483582  1.196128e-02  1.189603e-02  0.168879   -0.545508\n",
      "5096d134   475264  1.175553e-02  1.178532e-02  0.170236    0.253399\n",
      "711ee120   447450  1.106756e-02  1.399287e-02  0.214688   26.431427\n",
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      "e1eae715   421122  1.041634e-02  1.065248e-03  0.017366  -89.773299\n",
      "c6263d8a   397746  9.838144e-03  1.434888e-02  0.247661   45.849449\n",
      "84ebbcd4   388015  9.597450e-03  1.534698e-02  0.271531   59.906799\n",
      "be74e6fe   379729  9.392498e-03  1.004928e-02  0.181680    6.992667\n",
      "981edffc   361456  8.940520e-03  9.175440e-04  0.017427  -89.737242\n",
      "3bd9e8e7   359934  8.902874e-03  1.099348e-02  0.209680   23.482428\n",
      "f07e20f8   359464  8.891249e-03  5.921283e-03  0.113085  -33.403244\n",
      "3bb1ddd7   357957  8.853973e-03  4.390926e-03  0.084211  -50.407278\n",
      "0eb711ec   357223  8.835818e-03  1.042976e-02  0.200438   18.039566\n",
      "0bcabeaf   354422  8.766536e-03  1.081271e-03  0.020944  -87.665921\n",
      "779d90c2   344574  8.522948e-03  1.322755e-02  0.263537   55.199220\n",
      "36b67a2a   343402  8.493959e-03  2.371135e-03  0.047402  -72.084452\n",
      "fce66524   343261  8.490472e-03  1.335486e-02  0.267091   57.292329\n",
      "5db079b5   315606  7.806432e-03  7.566861e-03  0.164594   -3.068898\n",
      "aad45b01   303474  7.506351e-03  4.689103e-03  0.106075  -37.531525\n",
      "158e4944   287296  7.106192e-03  7.256886e-03  0.173407    2.120599\n",
      "a5bce124   279510  6.913607e-03  9.999904e-03  0.245608   44.640901\n",
      "...           ...           ...           ...       ...         ...\n",
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      "417e7adf        1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "0e8e071c        1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
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      "4d328265        1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "\n",
      "[8251 rows x 5 columns]\n",
      "\n",
      "device_type属性的取值和次数\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       特征分布           P_C         P_C|A     P_A|C     概率提升比%\n",
      "1  37304667  9.227213e-01  9.192987e-01  0.169176  -0.370923\n",
      "0   2220812  5.493121e-02  6.817050e-02  0.210731  24.101590\n",
      "4    774272  1.915142e-02  1.076465e-02  0.095444 -43.791912\n",
      "5    129185  3.195357e-03  1.765897e-03  0.093842 -44.735538\n",
      "2        31  7.667769e-07  2.913300e-07  0.064516 -62.005894\n",
      "\n",
      "device_conn_type属性的取值和次数\n",
      "       特征分布       P_C     P_C|A     P_A|C     概率提升比%\n",
      "0  34886838  0.862917  0.920441  0.181125   6.666255\n",
      "2   3317443  0.082056  0.065377  0.135289 -20.326881\n",
      "3   2181796  0.053966  0.013997  0.044043 -74.062924\n",
      "5     42890  0.001061  0.000185  0.029611 -82.562043\n",
      "\n",
      "C14属性的取值和次数\n",
      "         特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "4687   948215  2.345385e-02  3.444395e-02  0.249374   46.858400\n",
      "21611  907004  2.243451e-02  7.374874e-03  0.055820  -67.127096\n",
      "21189  765968  1.894602e-02  2.218624e-03  0.019885  -88.289762\n",
      "21191  765092  1.892435e-02  2.192404e-03  0.019672  -88.414904\n",
      "19771  730238  1.806225e-02  1.212151e-02  0.113956  -32.890328\n",
      "19772  729305  1.803917e-02  1.187243e-02  0.111757  -34.185287\n",
      "16208  657764  1.626962e-02  1.170783e-02  0.122194  -28.038731\n",
      "20108  587773  1.453841e-02  2.122004e-02  0.247846   45.958464\n",
      "8330   554444  1.371403e-02  1.194511e-02  0.147903  -12.898572\n",
      "19950  529145  1.308826e-02  9.582865e-03  0.124327  -26.782767\n",
      "15705  510276  1.262154e-02  1.535484e-02  0.206578   21.655806\n",
      "15701  506797  1.253549e-02  1.488697e-02  0.201659   18.758523\n",
      "15699  504923  1.248914e-02  1.478340e-02  0.200999   18.370027\n",
      "15703  503358  1.245043e-02  1.411596e-02  0.192521   13.377298\n",
      "15704  503315  1.244937e-02  1.482360e-02  0.202189   19.071134\n",
      "15707  502374  1.242609e-02  1.450416e-02  0.198203   16.723420\n",
      "15708  502189  1.242151e-02  1.416184e-02  0.193596   14.010614\n",
      "15702  485719  1.201413e-02  1.136347e-02  0.160609   -5.415781\n",
      "15706  477688  1.181549e-02  1.019393e-02  0.146501  -13.724011\n",
      "16615  438490  1.084594e-02  1.200309e-02  0.187922   10.669000\n",
      "23804  406539  1.005564e-02  4.497990e-03  0.075956  -55.268966\n",
      "21767  376105  9.302860e-03  5.665058e-03  0.103405  -39.104117\n",
      "21768  373692  9.243175e-03  5.678460e-03  0.104319  -38.565916\n",
      "17239  340800  8.429599e-03  9.012004e-03  0.181538    6.909037\n",
      "22676  340407  8.419879e-03  1.012590e-02  0.204211   20.261876\n",
      "19251  339308  8.392695e-03  3.840895e-03  0.077711  -54.235258\n",
      "17654  303748  7.513128e-03  1.761061e-02  0.398021  134.397847\n",
      "17653  301220  7.450598e-03  1.735002e-02  0.395422  132.867404\n",
      "6563   294504  7.284480e-03  1.030886e-02  0.240306   41.518124\n",
      "21790  280425  6.936240e-03  3.662893e-03  0.089671  -47.191952\n",
      "...       ...           ...           ...       ...         ...\n",
      "22076       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "21802       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "22976       1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "22080       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "22978       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "22237       1  2.473474e-08  1.456650e-07  1.000000  488.908643\n",
      "22345       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "22528       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "22567       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "21800       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "21785       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "23573       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "20473       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "18156       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "23554       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "7646        1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "7648        1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "7655        1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "7656        1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "23518       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "23425       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "21784       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "23360       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "21304       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "21305       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "23353       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "23339       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "21299       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "23260       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "21298       1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "\n",
      "[2626 rows x 5 columns]\n",
      "\n",
      "C15属性的取值和次数\n",
      "          特征分布       P_C     P_C|A     P_A|C      概率提升比%\n",
      "320   37708959  0.932721  0.871213  0.158608   -6.594496\n",
      "300    2337294  0.057812  0.122348  0.359358  111.628957\n",
      "216     298794  0.007391  0.005534  0.127138  -25.127474\n",
      "728      74533  0.001844  0.000618  0.056968  -66.451020\n",
      "120       3069  0.000076  0.000008  0.018899  -88.870413\n",
      "1024      2560  0.000063  0.000095  0.254688   49.987670\n",
      "480       2137  0.000053  0.000083  0.267665   57.630203\n",
      "768       1621  0.000040  0.000101  0.425663  150.676720\n",
      "\n",
      "C16属性的取值和次数\n",
      "          特征分布       P_C     P_C|A     P_A|C      概率提升比%\n",
      "50    38136554  0.943298  0.879466  0.158315   -6.766921\n",
      "250    1806334  0.044679  0.110865  0.421347  148.134756\n",
      "36      298794  0.007391  0.005534  0.127138  -25.127474\n",
      "480     103365  0.002557  0.003231  0.214560   26.356270\n",
      "90       74533  0.001844  0.000618  0.056968  -66.451020\n",
      "20        3069  0.000076  0.000008  0.018899  -88.870413\n",
      "768       2560  0.000063  0.000095  0.254688   49.987670\n",
      "320       2137  0.000053  0.000083  0.267665   57.630203\n",
      "1024      1621  0.000040  0.000101  0.425663  150.676720\n",
      "\n",
      "C17属性的取值和次数\n",
      "         特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "1722  4513492  1.116401e-01  1.246572e-01  0.189605   11.659938\n",
      "2424  1531071  3.787064e-02  4.411028e-03  0.019778  -88.352381\n",
      "2227  1473105  3.643687e-02  2.421142e-02  0.112832  -33.552413\n",
      "1800  1190161  2.943832e-02  2.133235e-02  0.123049  -27.535440\n",
      "423    948215  2.345385e-02  3.444395e-02  0.249374   46.858400\n",
      "2480   918663  2.272289e-02  7.504953e-03  0.056084  -66.971837\n",
      "2502   855087  2.115035e-02  2.454295e-02  0.197043   16.040389\n",
      "2528   824907  2.040386e-02  1.613284e-02  0.134261  -20.932422\n",
      "2506   803166  1.986610e-02  1.176070e-02  0.100525  -40.800151\n",
      "2374   756358  1.870832e-02  2.782639e-02  0.252566   48.738055\n",
      "2545   713546  1.764938e-02  2.335520e-02  0.224702   32.328774\n",
      "1872   695237  1.719651e-02  3.047808e-02  0.300953   77.234110\n",
      "1994   604968  1.496373e-02  3.496063e-02  0.396727  133.635823\n",
      "2299   587773  1.453841e-02  2.122004e-02  0.247846   45.958464\n",
      "2526   586936  1.451771e-02  1.030347e-02  0.120514  -29.028269\n",
      "1863   567425  1.403511e-02  1.339099e-02  0.162013   -4.589379\n",
      "761    558460  1.381336e-02  1.200367e-02  0.147559  -13.101018\n",
      "2333   512860  1.268546e-02  1.247665e-02  0.167010   -1.646079\n",
      "1993   495667  1.226019e-02  2.601271e-02  0.360280  112.172117\n",
      "2665   485332  1.200456e-02  5.380720e-03  0.076111  -55.177700\n",
      "2676   475926  1.177191e-02  9.299109e-03  0.134136  -21.005915\n",
      "1873   470663  1.164173e-02  9.680169e-03  0.141194  -16.849372\n",
      "2507   447398  1.106627e-02  5.638984e-03  0.086527  -49.043511\n",
      "2726   406539  1.005564e-02  4.497990e-03  0.075956  -55.268966\n",
      "2647   363865  9.000106e-03  1.508711e-02  0.284650   67.632566\n",
      "2566   361010  8.929489e-03  5.905843e-03  0.112307  -33.861356\n",
      "2667   356378  8.814917e-03  1.202858e-02  0.231712   36.457102\n",
      "1973   340800  8.429599e-03  9.012004e-03  0.181538    6.909037\n",
      "2616   340407  8.419879e-03  1.012590e-02  0.204211   20.261876\n",
      "2201   339308  8.392695e-03  3.840895e-03  0.077711  -54.235258\n",
      "...       ...           ...           ...       ...         ...\n",
      "2598      167  4.130702e-06  4.369951e-07  0.017964  -89.420803\n",
      "872       145  3.586537e-06  1.165320e-06  0.055172  -67.508489\n",
      "2459      136  3.363925e-06  1.310985e-06  0.066176  -61.028105\n",
      "2651      132  3.264986e-06  2.913300e-07  0.015152  -91.077142\n",
      "2568      132  3.264986e-06  2.330640e-06  0.121212  -28.617134\n",
      "1515      120  2.968169e-06  4.078621e-06  0.233333   37.412017\n",
      "2084      104  2.572413e-06  4.369951e-07  0.028846  -83.012251\n",
      "2719       94  2.325066e-06  5.098276e-06  0.372340  119.274495\n",
      "2375       80  1.978779e-06  1.456650e-07  0.012500  -92.638642\n",
      "2511       74  1.830371e-06  5.826601e-07  0.054054  -68.167100\n",
      "2737       66  1.632493e-06  1.602315e-06  0.166667   -1.848560\n",
      "2465       65  1.607758e-06  2.913300e-07  0.030769  -81.879734\n",
      "2722       63  1.558289e-06  2.330640e-06  0.253968   49.564100\n",
      "2758       50  1.236737e-06  1.019655e-06  0.140000  -17.552790\n",
      "2541       41  1.014124e-06  7.283251e-07  0.121951  -28.181873\n",
      "644        26  6.431032e-07  0.000000e+00  0.000000 -100.000000\n",
      "2346       23  5.688990e-07  0.000000e+00  0.000000 -100.000000\n",
      "2521       15  3.710211e-07  2.913300e-07  0.133333  -21.478848\n",
      "2585       13  3.215516e-07  1.456650e-07  0.076923  -54.699335\n",
      "2448       12  2.968169e-07  0.000000e+00  0.000000 -100.000000\n",
      "2447        8  1.978779e-07  1.456650e-07  0.125000  -26.386420\n",
      "2575        8  1.978779e-07  0.000000e+00  0.000000 -100.000000\n",
      "2718        7  1.731432e-07  0.000000e+00  0.000000 -100.000000\n",
      "2744        5  1.236737e-07  2.913300e-07  0.400000  135.563457\n",
      "2567        5  1.236737e-07  5.826601e-07  0.800000  371.126914\n",
      "2746        4  9.893896e-08  1.456650e-07  0.250000   47.227161\n",
      "1253        3  7.420422e-08  0.000000e+00  0.000000 -100.000000\n",
      "2704        1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "2752        1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "1516        1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "\n",
      "[435 rows x 5 columns]\n",
      "\n",
      "C18属性的取值和次数\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       特征分布       P_C     P_C|A     P_A|C     概率提升比%\n",
      "0  16939044  0.418983  0.390407  0.158225  -6.820216\n",
      "3  13654242  0.337734  0.290293  0.145953 -14.046826\n",
      "2   7116058  0.176014  0.305760  0.294976  73.713806\n",
      "1   2719623  0.067269  0.013539  0.034176 -79.873206\n",
      "\n",
      "C19属性的取值和次数\n",
      "          特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "35    12170630  3.010374e-01  2.957149e-01  0.166803   -1.768059\n",
      "39     8829426  2.183936e-01  3.140276e-01  0.244163   43.789758\n",
      "167    3145695  7.780795e-02  7.414481e-02  0.161811   -4.707926\n",
      "161    1587765  3.927295e-02  5.359745e-03  0.023174  -86.352581\n",
      "47     1451708  3.590762e-02  3.748456e-02  0.177263    4.391666\n",
      "1327   1092601  2.702520e-02  3.691210e-02  0.231927   36.583991\n",
      "297    1014859  2.510227e-02  1.078373e-02  0.072947  -57.040835\n",
      "163     926864  2.292574e-02  1.274962e-02  0.094433  -44.387303\n",
      "175     811516  2.007264e-02  1.444575e-02  0.122205  -28.032646\n",
      "679     737468  1.824108e-02  1.196638e-02  0.111395  -34.398720\n",
      "935     704359  1.742214e-02  1.220221e-02  0.118929  -29.961443\n",
      "687     555698  1.374505e-02  1.524530e-02  0.188340   10.914883\n",
      "1063    522944  1.293488e-02  2.708481e-02  0.355562  109.393518\n",
      "41      513229  1.269459e-02  7.750545e-03  0.103673  -38.946063\n",
      "33      478227  1.182882e-02  4.293185e-03  0.061630  -63.705720\n",
      "431     430005  1.063606e-02  1.543729e-02  0.246458   45.141010\n",
      "803     406539  1.005564e-02  4.497990e-03  0.075956  -55.268966\n",
      "1319    394524  9.758449e-03  1.316841e-02  0.229142   34.943677\n",
      "303     328180  8.117447e-03  1.498238e-02  0.313410   84.570048\n",
      "419     325027  8.039458e-03  1.990367e-03  0.042040  -75.242525\n",
      "171     306934  7.591933e-03  4.528289e-03  0.101282  -40.353943\n",
      "169     291959  7.221530e-03  5.171400e-03  0.121599  -28.389142\n",
      "299     291844  7.218686e-03  3.190647e-03  0.075054  -55.800171\n",
      "427     270146  6.681991e-03  2.586428e-03  0.065727  -61.292553\n",
      "34      263275  6.512039e-03  5.254429e-03  0.137013  -19.312078\n",
      "291     259205  6.411368e-03  7.927382e-03  0.209957   23.645710\n",
      "547     247633  6.125138e-03  5.141101e-03  0.142525  -16.065542\n",
      "43      212757  5.262489e-03  2.859259e-03  0.092260  -45.667180\n",
      "815     208331  5.153013e-03  3.423565e-03  0.112816  -33.561881\n",
      "38      182787  4.521189e-03  4.643510e-03  0.174400    2.705497\n",
      "...        ...           ...           ...       ...         ...\n",
      "559      85122  2.105471e-03  1.338516e-03  0.107951  -36.426758\n",
      "813      60918  1.506791e-03  9.992621e-04  0.112610  -33.682766\n",
      "551      52348  1.294814e-03  1.007565e-03  0.132135  -22.184590\n",
      "681      48395  1.197038e-03  8.113542e-04  0.115095  -32.219834\n",
      "290      44822  1.108661e-03  9.112804e-04  0.139574  -17.803479\n",
      "1315     39870  9.861741e-04  3.498874e-04  0.060246  -64.520728\n",
      "801      29418  7.276466e-04  3.632886e-04  0.084778  -50.073487\n",
      "295      27526  6.808485e-04  1.396928e-04  0.034840  -79.482548\n",
      "673      24745  6.120611e-04  3.134711e-04  0.086967  -48.784344\n",
      "1831     23662  5.852734e-04  3.217740e-04  0.093356  -45.021588\n",
      "423      23111  5.716446e-04  2.199542e-04  0.065337  -61.522563\n",
      "1071     21210  5.246238e-04  1.464807e-03  0.474116  179.211000\n",
      "1575     19196  4.748081e-04  3.436238e-04  0.122890  -27.628908\n",
      "943      19128  4.731261e-04  2.445716e-04  0.087777  -48.307319\n",
      "1835     18756  4.639248e-04  3.367775e-04  0.123267  -27.406868\n",
      "425      17705  4.379286e-04  2.116513e-04  0.082067  -51.669909\n",
      "1839     11315  2.798736e-04  1.564442e-04  0.094918  -44.101822\n",
      "555       8954  2.214749e-04  2.511265e-04  0.192540   13.388262\n",
      "553       8087  2.000298e-04  5.389606e-05  0.045752  -73.055991\n",
      "417       6507  1.609490e-04  3.714458e-05  0.039189  -76.921515\n",
      "289       5788  1.431647e-04  8.434005e-05  0.100035  -41.088786\n",
      "939       5421  1.340870e-04  2.311704e-04  0.292750   72.403250\n",
      "1583      3477  8.600269e-05  4.836079e-05  0.095485  -43.768286\n",
      "45        3269  8.085787e-05  1.165320e-05  0.024472  -85.588042\n",
      "683        808  1.998567e-05  1.034222e-05  0.087871  -48.251840\n",
      "1447       161  3.982293e-06  8.157241e-06  0.347826  104.837789\n",
      "1195       132  3.264986e-06  2.913300e-07  0.015152  -91.077142\n",
      "545        117  2.893965e-06  2.767635e-06  0.162393   -4.365263\n",
      "677          8  1.978779e-07  0.000000e+00  0.000000 -100.000000\n",
      "1959         2  4.946948e-08  1.456650e-07  0.500000  194.454321\n",
      "\n",
      "[68 rows x 5 columns]\n",
      "\n",
      "C20属性的取值和次数\n",
      "                特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "4294967295  18937918  4.684245e-01  5.318365e-01  0.192793   13.537308\n",
      "100084       2438478  6.031512e-02  7.598936e-02  0.213933   25.987255\n",
      "100148       1794890  4.439614e-02  6.092862e-02  0.233039   37.238560\n",
      "100111       1716733  4.246294e-02  2.178450e-02  0.087114  -48.697634\n",
      "100077       1575495  3.896946e-02  4.027084e-02  0.175476    3.339497\n",
      "100075       1546414  3.825015e-02  3.696381e-02  0.164095   -3.362962\n",
      "100081       1337033  3.307116e-02  3.687102e-02  0.189316   11.489943\n",
      "100083       1073567  2.655440e-02  3.020597e-02  0.193156   13.751289\n",
      "100156       1032558  2.554005e-02  1.438209e-02  0.095621  -43.688097\n",
      "100193        707521  1.750035e-02  2.296263e-03  0.022281  -86.878756\n",
      "100176        649479  1.606469e-02  1.125612e-02  0.118978  -29.932567\n",
      "100074        587455  1.453055e-02  1.407415e-02  0.164472   -3.140916\n",
      "100079        578206  1.430178e-02  1.168379e-02  0.138722  -18.305306\n",
      "100189        476733  1.179187e-02  1.893937e-03  0.027273  -83.938619\n",
      "100076        457895  1.132591e-02  9.673323e-03  0.145029  -14.591238\n",
      "100192        234785  5.807346e-03  1.037135e-03  0.030326  -82.140982\n",
      "100190        225665  5.581765e-03  7.522142e-04  0.022883  -86.523722\n",
      "100191        223351  5.524529e-03  2.712720e-03  0.083380  -50.896814\n",
      "100188        220499  5.453986e-03  4.182480e-03  0.130218  -23.313331\n",
      "100013        198110  4.900199e-03  3.658086e-03  0.126763  -25.348227\n",
      "100031        185730  4.593983e-03  5.124787e-03  0.189426   11.554320\n",
      "100155        161718  4.000053e-03  3.644102e-03  0.154695   -8.898654\n",
      "100194        146924  3.634127e-03  1.792991e-03  0.083778  -50.662407\n",
      "100181        142366  3.521386e-03  2.570114e-03  0.123934  -27.014146\n",
      "100000        139980  3.462369e-03  1.823289e-03  0.089420  -47.339838\n",
      "100233        118568  2.932749e-03  2.937772e-03  0.170096    0.171290\n",
      "100105        117297  2.901311e-03  2.140256e-03  0.125263  -26.231407\n",
      "100182        116845  2.890131e-03  2.298885e-03  0.135068  -20.457391\n",
      "100003        115705  2.861933e-03  7.879021e-04  0.046748  -72.469583\n",
      "100119        113055  2.796386e-03  2.926119e-03  0.177683    4.639307\n",
      "...              ...           ...           ...       ...         ...\n",
      "100043          1362  3.368872e-05  2.214108e-05  0.111601  -34.277450\n",
      "100244          1267  3.133892e-05  2.563704e-05  0.138911  -18.194222\n",
      "100163          1105  2.733189e-05  1.835379e-05  0.114027  -32.848426\n",
      "100010          1003  2.480894e-05  2.709369e-05  0.185444    9.209379\n",
      "100178           928  2.295384e-05  1.981044e-05  0.146552  -13.694423\n",
      "100024           825  2.040616e-05  1.121621e-05  0.093333  -45.035193\n",
      "100213           768  1.899628e-05  2.563704e-05  0.229167   34.958231\n",
      "100109           729  1.803163e-05  8.157241e-06  0.076818  -54.761476\n",
      "100122           691  1.709171e-05  9.759557e-06  0.096961  -42.898873\n",
      "100082           630  1.558289e-05  7.428916e-06  0.080952  -52.326443\n",
      "100108           589  1.456876e-05  4.224286e-06  0.049236  -71.004498\n",
      "100169           537  1.328256e-05  6.263596e-06  0.080074  -52.843442\n",
      "100137           507  1.254051e-05  1.747980e-05  0.236686   39.386661\n",
      "100153           472  1.167480e-05  8.739901e-06  0.127119  -25.138732\n",
      "100175           196  4.848009e-06  7.574581e-06  0.265306   56.241068\n",
      "100098           120  2.968169e-06  1.602315e-06  0.091667  -46.016708\n",
      "100138           102  2.522944e-06  2.330640e-06  0.156863   -7.622174\n",
      "100100            79  1.954044e-06  3.641626e-06  0.316456   86.363495\n",
      "100186            44  1.088329e-06  5.826601e-07  0.090909  -46.462851\n",
      "100078            43  1.063594e-06  1.456650e-06  0.232558   36.955498\n",
      "100157            29  7.173075e-07  1.456650e-07  0.034483  -79.692805\n",
      "100246            28  6.925727e-07  2.913300e-07  0.071429  -57.935097\n",
      "100027            23  5.688990e-07  0.000000e+00  0.000000 -100.000000\n",
      "100132             7  1.731432e-07  0.000000e+00  0.000000 -100.000000\n",
      "100134             6  1.484084e-07  1.456650e-07  0.166667   -1.848560\n",
      "100006             5  1.236737e-07  2.913300e-07  0.400000  135.563457\n",
      "100187             3  7.420422e-08  0.000000e+00  0.000000 -100.000000\n",
      "100008             2  4.946948e-08  0.000000e+00  0.000000 -100.000000\n",
      "100209             2  4.946948e-08  0.000000e+00  0.000000 -100.000000\n",
      "100198             1  2.473474e-08  0.000000e+00  0.000000 -100.000000\n",
      "\n",
      "[172 rows x 5 columns]\n",
      "\n",
      "C21属性的取值和次数\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        特征分布       P_C     P_C|A     P_A|C      概率提升比%\n",
      "23   8896205  0.220045  0.275947  0.212944   25.404597\n",
      "221  5051245  0.124941  0.123378  0.167681   -1.251421\n",
      "79   4614799  0.114146  0.126204  0.187744   10.564214\n",
      "48   2160794  0.053447  0.043453  0.138056  -18.697513\n",
      "71   2108496  0.052153  0.008661  0.028201  -83.392382\n",
      "61   2053636  0.050796  0.019720  0.065921  -61.178478\n",
      "157  1856105  0.045910  0.031191  0.115366  -32.060095\n",
      "32   1783343  0.044111  0.059836  0.230343   35.651123\n",
      "33   1497559  0.037042  0.085930  0.393919  131.982326\n",
      "52   1203050  0.029757  0.047446  0.270743   59.442713\n",
      "42   1018906  0.025202  0.017517  0.118025  -30.494277\n",
      "51    850249  0.021031  0.022970  0.185462    9.220258\n",
      "15    766986  0.018971  0.023561  0.210885   24.192120\n",
      "212   659994  0.016325  0.004982  0.051820  -69.482655\n",
      "43    588961  0.014568  0.006496  0.075715  -55.410964\n",
      "117   419943  0.010387  0.012583  0.205702   21.139524\n",
      "229   406539  0.010056  0.004498  0.075956  -55.268966\n",
      "13    384314  0.009506  0.011902  0.212600   25.201738\n",
      "16    347178  0.008587  0.013123  0.259501   52.822317\n",
      "156   334906  0.008284  0.003431  0.070324  -58.585465\n",
      "68    324148  0.008018  0.005614  0.118906  -29.975487\n",
      "159   290215  0.007178  0.004933  0.116689  -31.280633\n",
      "95    276988  0.006851  0.004987  0.123608  -27.206037\n",
      "46    235809  0.005833  0.003396  0.098877  -41.770696\n",
      "246   201746  0.004990  0.001361  0.046326  -72.718467\n",
      "69    176226  0.004359  0.003535  0.137710  -18.901666\n",
      "91    169042  0.004181  0.002308  0.093728  -44.802661\n",
      "17    166268  0.004113  0.002200  0.090817  -46.516946\n",
      "111   140305  0.003470  0.002097  0.102626  -39.562414\n",
      "76    138160  0.003417  0.001020  0.050673  -70.158154\n",
      "70    133539  0.003303  0.003351  0.172279    1.456745\n",
      "90    128679  0.003183  0.003934  0.209894   23.608619\n",
      "110   121407  0.003003  0.001135  0.064189  -62.198514\n",
      "171   115845  0.002865  0.001640  0.097173  -42.774012\n",
      "204    92782  0.002295  0.000491  0.036322  -78.609837\n",
      "101    81352  0.002012  0.001181  0.099703  -41.284320\n",
      "253    78375  0.001939  0.002083  0.182456    7.449998\n",
      "112    74532  0.001844  0.001192  0.109792  -35.342679\n",
      "82     71393  0.001766  0.002767  0.266091   56.703003\n",
      "100    65258  0.001614  0.001098  0.115511  -31.974726\n",
      "178    50055  0.001238  0.000532  0.073000  -57.009846\n",
      "182    49761  0.001231  0.000795  0.109684  -35.405973\n",
      "108    46723  0.001156  0.000990  0.145389  -14.379291\n",
      "35     46707  0.001155  0.001935  0.284454   67.517508\n",
      "94     22206  0.000549  0.000528  0.163244   -3.864098\n",
      "251    21170  0.000524  0.000320  0.103684  -38.939326\n",
      "116    16189  0.000400  0.000328  0.139045  -18.115180\n",
      "194    14032  0.000347  0.000305  0.149088  -12.200906\n",
      "20     13365  0.000331  0.000175  0.090086  -46.947549\n",
      "93     12411  0.000307  0.000171  0.094755  -44.198166\n",
      "102     8954  0.000221  0.000251  0.192540   13.388262\n",
      "104     8425  0.000208  0.000084  0.068249  -59.807422\n",
      "126     7780  0.000192  0.000074  0.065296  -61.546839\n",
      "163     6507  0.000161  0.000037  0.039189  -76.921515\n",
      "177     5618  0.000139  0.000065  0.078854  -53.562384\n",
      "255     4608  0.000114  0.000132  0.196615   15.788027\n",
      "195     3890  0.000096  0.000035  0.062468  -63.212134\n",
      "1       3027  0.000075  0.000061  0.137430  -19.066404\n",
      "219     1765  0.000044  0.000018  0.068555  -59.627226\n",
      "85       497  0.000012  0.000010  0.144869  -14.685267\n"
     ]
    }
   ],
   "source": [
    "var=[ 'hour', 'C1', 'banner_pos', 'site_id', 'site_domain',\n",
    "       'site_category', 'app_id', 'app_domain', 'app_category', 'device_id',\n",
    "       'device_ip', 'device_model', 'device_type', 'device_conn_type', 'C14',\n",
    "       'C15', 'C16', 'C17', 'C18', 'C19', 'C20', 'C21']\n",
    "#筛选出点击率为1的事件\n",
    "train_df_click=df[df['click']==1]\n",
    "for v in var:\n",
    "    print('\\n%s属性的取值和次数'%v)\n",
    "    P=pd.concat([df[v].value_counts(),df[v].value_counts(normalize=True),\\\n",
    "                   train_df_click[v].value_counts(normalize=True)],\\\n",
    "                   axis=1,join_axes=[df[v].value_counts().index],keys=['特征分布','P_C','P_C|A']).fillna(0)\n",
    "    #P(A│ci)=(P(ci│A)P(A))/(P(ci))\n",
    "    P['P_A|C']=(P['P_C|A']*P_A)/P['P_C']\n",
    "    P['概率提升比%']=(P['P_A|C']-P_A)*100/P_A\n",
    "    print(P)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6、观察每类特征的CTR的平均值，并显示top 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for cat in df.columns:\n",
    "    if cat not in ['id', 'click', 'hour', 'device_id', 'device_ip',\n",
    "                   'device_model'] and 'id' not in cat and 'domain' not in cat and 'ip' not in cat:\n",
    "        gb = df.groupby(cat)['click'].mean().sort_values(ascending=False).head(10)\n",
    "        plot = gb.plot(kind='bar', title='Scores', figsize=(20, 5))\n",
    "        plot.set_ylim(0, np.max(gb.values) + 0.05)\n",
    "        plt.title('Mean CTR top 10 values for variable %s' % cat, fontsize=15)\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "7、将\"hour\"字段分为\"小时\"、\"天\"、\"周\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_date(x_):\n",
    "    return int(str(x_)[:6])\n",
    "\n",
    "\n",
    "def get_day(x_):\n",
    "    return dict_day[str(x_)[4:6]]\n",
    "\n",
    "\n",
    "def get_hour(x_):\n",
    "    return int(str(x_)[6:])\n",
    "\n",
    "\n",
    "dict_day = {'21': 2, '22': 3, '23': 4, '24': 5, '25': 6, '26': 0, '27': 1, '28': 2, '29': 3, '30': 4, '31': 5}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "8、每天的CTR平均值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['date'] = df['hour'].map(get_date)\n",
    "gb = df.groupby('date')['click'].mean()\n",
    "plot = gb.plot(kind='bar', title='Scores', figsize=(20, 5))\n",
    "plot.set_ylim(0, np.max(gb.values) + 0.02)\n",
    "plt.title('Mean CTR through the days', fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "9、一个星期中每天的CTR平均值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['day'] = df['hour'].map(get_day)\n",
    "gb = df.groupby('day')['click'].mean()\n",
    "plot = gb.plot(kind='bar', title='Scores', figsize=(20, 5))\n",
    "plot.set_ylim(0, np.max(gb.values) + 0.02)\n",
    "plt.title('Mean CTR through weekdays', fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "10、一天中每小时的CTR平均值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['day'] = df['hour'].map(get_hour)\n",
    "gb = df.groupby('day')['click'].mean()\n",
    "plot = gb.plot(kind='bar', title='Scores', figsize=(20, 5))\n",
    "plot.set_ylim(0, np.max(gb.values) + 0.02)\n",
    "plt.title('Mean CTR through hours', fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 中间结论：\n",
    "\n",
    "1）类别特征以及其组合包含有CTR信息 \n",
    "2）'hour'字段应该以星期和小时的方式进行处理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "12、分析\"site_id\"和\"app_id\"两者对用户行为的影响\n",
    "\n",
    "（1）按照\"site_id\"字段中的不同类别进行分组并计数，并显示top 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "site_id\n",
       "85f751fd    14596137\n",
       "1fbe01fe     6486150\n",
       "e151e245     2637747\n",
       "d9750ee7      963745\n",
       "5b08c53b      913325\n",
       "5b4d2eda      771360\n",
       "856e6d3f      765891\n",
       "a7853007      461311\n",
       "b7e9786d      369099\n",
       "5ee41ff2      349008\n",
       "Name: click, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('site_id')['click'].count().sort_values(ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "（2）按照\"app_id\"字段中的不同类别进行分组并计数，并显示top 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "app_id\n",
       "ecad2386    25832830\n",
       "92f5800b     1555283\n",
       "e2fcccd2     1129016\n",
       "febd1138      759098\n",
       "9c13b419      757812\n",
       "7358e05e      615635\n",
       "a5184c22      491457\n",
       "d36838b1      457572\n",
       "685d1c4c      408515\n",
       "54c5d545      397693\n",
       "Name: click, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('app_id')['click'].count().sort_values(ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "（3）计算site_id为85f751fd占总数据的比例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.3610316583156824\n"
     ]
    }
   ],
   "source": [
    "var1 = df[df['site_id'] == '85f751fd'].shape[0] / df.shape[0]\n",
    "print(var1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "（4）计算app_id为ecad2386占总数据的比例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6389683416843176\n"
     ]
    }
   ],
   "source": [
    "var2 = df[df['app_id'] == 'ecad2386'].shape[0] / df.shape[0]\n",
    "print(var2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "（5）3）和4）的比例之和"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0\n"
     ]
    }
   ],
   "source": [
    "var3 = df[df['site_id'] == '85f751fd'].shape[0] / df.shape[0] + df[df['app_id'] == 'ecad2386'].shape[0] / df.shape[0]\n",
    "print(var3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 中间结论\n",
    "'site_id'为85f751fd)占总数据量的33%,'app_id为ecad2386占总数据量的67%。因此,可以得到以下结论,即'site_id'为85f751fd代表mobile\n",
    "用户, 'app_id'为ecad2386代表app用户，同时就意味着两者不回同时出现，也就意味着“app_id”和“si te_id”两个特征需要给予重点关注。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "13、mobile用户的平均CTR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.11882644017386244"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['site_id'] == '85f751fd']['click'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "14、app用户的平均CTR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.19861002453080054"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['site_id'] != '85f751fd']['click'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "15、app用户和mobile用户的平均ctr比较"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ThEgAAAAATBIiAQAAADBJiAQAAADAJCESAAAAAJOESAAAAABMEiIBAAAAMEmIBAAAAMAkIRIAAAAAk4RIAAAAAExaKESqqkOr6pKq2lhVJy5z/ISquriqPl5V762q+8wcO6aqPjm+jplpf0BVXTBe88+rqlbmlgAAAABYaZMhUlXtkeSUJI9LclCSJ1fVQXPdPpZkXXf/aJK3JvmT8dy7J3lekgclOSTJ86rqbuM5f5Xkl5McOL4OvdV3AwAAAMB2schIpEOSbOzuS7v7hiSnJTl8tkN3v6+7vz7unpNk33H7sUnO7O6ru/tLSc5McmhV3SvJnbv7nO7uJK9N8vgVuB8AAAAAtoNFQqR9klw+s3/F2LY5T0vy7olz9xm3J69ZVcdV1Yaq2rBp06YFygUAAABgpa3owtpV9QtJ1iV58Upds7tP7e513b1u7dq1K3VZAAAAALbCmgX6XJlkv5n9fce2m6mqRyV5TpKHdff1M+c+fO7cs8f2fefab3FN2Fb7n/iu1S4BuA267I9/erVLAACAVbPISKTzkhxYVQdU1Z5JjkqyfrZDVf1YkpclOay7vzBz6Iwkj6mqu40Laj8myRnd/bkkX6mqB49PZXtKkneswP0AAAAAsB1MjkTq7hur6vgMgdAeSV7Z3RdV1clJNnT3+gzT174zyVuGTCif7e7Duvvqqvr9DEFUkpzc3VeP289I8uokd8iwhtK7AwAAAMBOaZHpbOnu05OcPtd20sz2o7Zw7iuTvHKZ9g1J7r9wpQAAAACsmhVdWBsAAACA2yYhEgAAAACThEgAAAAATBIiAQAAADBJiAQAAADAJCESAAAAAJOESAAAAABMEiIBAAAAMEmIBAAAAMAkIRIAAAAAk4RIAAAAAEwSIgEAAAAwSYgEAAAAwCQhEgAAAACThEgAAAAATBIiAQAAADBJiAQAAADAJCESAAAAAJOESAAAAABMEiIBAAAAMEmIBAAAAMAkIRIAAAAAkxYKkarq0Kq6pKo2VtWJyxx/aFV9tKpurKojZtp/qqrOn3ldV1WPH4+9uqo+PXPs4JW7LQAAAABW0pqpDlW1R5JTkjw6yRVJzquq9d198Uy3zyY5NskzZ8/t7vclOXi8zt2TbEzyDzNdntXdb701NwAAAADA9jcZIiU5JMnG7r40SarqtCSHJ/nPEKm7LxuP3bSF6xyR5N3d/fVtrhYAAACAVbHIdLZ9klw+s3/F2La1jkryt3Ntf1BVH6+ql1TVXsudVFXHVdWGqtqwadOmbXhbAAAAAG6tHbKwdlXdK8mPJDljpvnZSX4wyQOT3D3J7y13bnef2t3runvd2rVrt3utAAAAANzSIiHSlUn2m9nfd2zbGk9M8vbu/uZSQ3d/rgfXJ3lVhmlzAAAAAOyEFgmRzktyYFUdUFV7ZpiWtn4r3+fJmZvKNo5OSlVVkscnuXArrwkAAADADjIZInX3jUmOzzAV7RNJ3tzdF1XVyVV1WJJU1QOr6ookRyZ5WVVdtHR+Ve2fYSTT++cu/YaquiDJBUn2TvLCW387AAAAAGwPizydLd19epLT59pOmtk+L8M0t+XOvSzLLMTd3Y/YmkIBAAAAWD07ZGFtAAAAAHZtQiQAAAAAJgmRAAAAAJgkRAIAAABgkhAJAAAAgElCJAAAAAAmCZEAAAAAmCREAgAAAGCSEAkAAACASUIkAAAAACYJkQAAAACYJEQCAAAAYJIQCQAAAIBJQiQAAAAAJgmRAAAAAJgkRAIAAABgkhAJAAAAgElCJAAAAAAmCZEAAAAAmCREAgAAAGCSEAkAAACASUIkAAAAACYJkQAAAACYtFCIVFWHVtUlVbWxqk5c5vhDq+qjVXVjVR0xd+xbVXX++Fo/035AVZ07XvNNVbXnrb8dAAAAALaHyRCpqvZIckqSxyU5KMmTq+qguW6fTXJskjcuc4lvdPfB4+uwmfYXJXlJd983yZeSPG0b6gcAAABgB1hkJNIhSTZ296XdfUOS05IcPtuhuy/r7o8nuWmRN62qSvKIJG8dm16T5PELVw0AAADADrVIiLRPkstn9q8Y2xb1HVW1oarOqaqloOgeSb7c3TdOXbOqjhvP37Bp06ateFsAAAAAVsqaHfAe9+nuK6vq+5KcVVUXJLlm0ZO7+9QkpybJunXrejvVCAAAAMAWLDIS6cok+83s7zu2LaS7rxx/Xprk7CQ/luSqJHetqqUQa6uuCQAAAMCOtUiIdF6SA8enqe2Z5Kgk6yfOSZJU1d2qaq9xe+8kD0lycXd3kvclWXqS2zFJ3rG1xQMAAACwY0yGSOO6RccnOSPJJ5K8ubsvqqqTq+qwJKmqB1bVFUmOTPKyqrpoPP2Hkmyoqn/NEBr9cXdfPB77vSQnVNXGDGskvWIlbwwAAACAlbPQmkjdfXqS0+faTprZPi/DlLT58z6U5Ec2c81LMzz5DQAAAICd3CLT2QAAAADYzQmRAAAAAJgkRAIAAABgkhAJAAAAgElCJAAAAAAmCZEAAAAAmCREAgAAAGCSEAkAAACASUIkAAAAACYJkQAAAACYJEQCAAAAYJIQCQAAAIBJQiQAAAAAJgmRAAAAAJgkRAIAAABgkhAJAAAAgElCJAAAAAAmCZEAAAAAmCREAgAAAGCSEAkAAACASUIkAAAAACYJkQAAAACYtFCIVFWHVtUlVbWxqk5c5vhDq+qjVXVjVR0x035wVf1LVV1UVR+vqifNHHt1VX26qs4fXwevzC0BAAAAsNLWTHWoqj2SnJLk0UmuSHJeVa3v7otnun02ybFJnjl3+teTPKW7P1lV35vkI1V1Rnd/eTz+rO5+6629CQAAAAC2r8kQKckhSTZ296VJUlWnJTk8yX+GSN192XjsptkTu/vfZrb/vaq+kGRtki8HAAAAgF3GItPZ9kly+cz+FWPbVqmqQ5LsmeRTM81/ME5ze0lV7bWZ846rqg1VtWHTpk1b+7YAAAAArIAdsrB2Vd0ryeuSPLW7l0YrPTvJDyZ5YJK7J/m95c7t7lO7e113r1u7du2OKBcAAACAOYuESFcm2W9mf9+xbSFVdeck70rynO4+Z6m9uz/Xg+uTvCrDtDkAAAAAdkKLhEjnJTmwqg6oqj2THJVk/SIXH/u/Pclr5xfQHkcnpaoqyeOTXLg1hQMAAACw40yGSN19Y5Ljk5yR5BNJ3tzdF1XVyVV1WJJU1QOr6ookRyZ5WVVdNJ7+xCQPTXJsVZ0/vg4ej72hqi5IckGSvZO8cEXvDAAAAIAVs8jT2dLdpyc5fa7tpJnt8zJMc5s/7/VJXr+Zaz5iqyoFAAAAYNXskIW1AQAAANi1LTQSCQAA2E6ef5fVrgC4LXr+NatdAbdBRiIBAAAAMEmIBAAAAMAkIRIAAAAAk4RIAAAAAEwSIgEAAAAwSYgEAAAAwCQhEgAAAACThEgAAAAATBIiAQAAADBJiAQAAADAJCESAAAAAJOESAAAAABMEiIBAAAAMEmIBAAAAMAkIRIAAAAAk4RIAAAAAEwSIgEAAAAwSYgEAAAAwCQhEgAAAACThEgAAAAATFooRKqqQ6vqkqraWFUnLnP8oVX10aq6saqOmDt2TFV9cnwdM9P+gKq6YLzmn1dV3frbAQAAAGB7mAyRqmqPJKckeVySg5I8uaoOmuv22STHJnnj3Ll3T/K8JA9KckiS51XV3cbDf5Xkl5McOL4O3ea7AAAAAGC7WmQk0iFJNnb3pd19Q5LTkhw+26G7L+vujye5ae7cxyY5s7uv7u4vJTkzyaFVda8kd+7uc7q7k7w2yeNv7c0AAAAAsH0sEiLtk+Tymf0rxrZFbO7cfcbtyWtW1XFVtaGqNmzatGnBtwUAAABgJe30C2t396ndva67161du3a1ywEAAADYLS0SIl2ZZL+Z/X3HtkVs7twrx+1tuSYAAAAAO9giIdJ5SQ6sqgOqas8kRyVZv+D1z0jymKq627ig9mOSnNHdn0vylap68PhUtqckecc21A8AAADADjAZInX3jUmOzxAIfSLJm7v7oqo6uaoOS5KqemBVXZHkyCQvq6qLxnOvTvL7GYKo85KcPLYlyTOS/E2SjUk+leTdK3pnAAAAAKyYNYt06u7Tk5w+13bSzPZ5ufn0tNl+r0zyymXaNyS5/9YUCwAAAMDq2OkX1gYAAABg9QmRAAAAAJgkRAIAAABgkhAJAAAAgElCJAAAAAAmCZEAAAAAmCREAgAAAGCSEAkAAACASUIkAAAAACYJkQAAAACYJEQCAAAAYJIQCQAAAIBJQiQAAAAAJgmRAAAAAJgkRAIAAABgkhAJAAAAgElCJAAAAAAmCZEAAAAAmCREAgAAAGCSEAkAAACASUIkAAAAACYJkQAAAACYtFCIVFWHVtUlVbWxqk5c5vheVfWm8fi5VbX/2H50VZ0/87qpqg4ej509XnPp2D1X8sYAAAAAWDmTIVJV7ZHklCSPS3JQkidX1UFz3Z6W5Evdfd8kL0nyoiTp7jd098HdfXCSX0zy6e4+f+a8o5eOd/cXVuB+AAAAANgOFhmJdEiSjd19aXffkOS0JIfP9Tk8yWvG7bcmeWRV1VyfJ4/nAgAAALCLWSRE2ifJ5TP7V4xty/bp7huTXJPkHnN9npTkb+faXjVOZXvuMqFTkqSqjquqDVW1YdOmTQuUCwAAAMBK2yELa1fVg5J8vbsvnGk+urt/JMlPjq9fXO7c7j61u9d197q1a9fugGoBAAAAmLdIiHRlkv1m9vcd25btU1VrktwlyVUzx4/K3Cik7r5y/HltkjdmmDYHAAAAwE5okRDpvCQHVtUBVbVnhkBo/Vyf9UmOGbePSHJWd3eSVNXtkjwxM+shVdWaqtp73L59kv+R5MIAAAAAsFNaM9Whu2+squOTnJFkjySv7O6LqurkJBu6e32SVyR5XVVtTHJ1hqBpyUOTXN7dl8607ZXkjDFA2iPJPyZ5+YrcEQAAAAArbjJESpLuPj3J6XNtJ81sX5fkyM2ce3aSB8+1fS3JA7ayVgAAAABWyQ5ZWBsAAACAXZsQCQAAAIBJQiQAAAAAJgmRAAAAAJgkRAIAAABgkhAJAAAAgElCJAAAAAAmCZEAAAAAmCREAgAAAGCSEAkAAACASUIkAAAAACYJkQAAAACYJEQCAAAAYJIQCQAAAIBJQiQAAAAAJgmRAAAAAJgkRAIAAABgkhAJAAAAgElCJAAAAAAmCZEAAAAAmCREAgAAAGCSEAkAAACASQuFSFV1aFVdUlUbq+rEZY7vVVVvGo+fW1X7j+37V9U3qur88fXXM+c8oKouGM/586qqlbopAAAAAFbWZIhUVXskOSXJ45IclOTJVXXQXLenJflSd983yUuSvGjm2Ke6++Dx9asz7X+V5JeTHDi+Dt322wAAAABge1pkJNIhSTZ296XdfUOS05IcPtfn8CSvGbffmuSRWxpZVFX3SnLn7j6nuzvJa5M8fqurBwAAAGCHWCRE2ifJ5TP7V4xty/bp7huTXJPkHuOxA6rqY1X1/qr6yZn+V0xcM0lSVcdV1Yaq2rBp06YFygUAAABgpW3vhbU/l+Te3f1jSU5I8saquvPWXKC7T+3udd29bu3atdulSAAAAAC2bJEQ6cok+83s7zu2LdunqtYkuUuSq7r7+u6+Kkm6+yNJPpXkB8b++05cEwAAAICdxCIh0nlJDqyqA6pqzyRHJVk/12d9kmPG7SOSnNXdXVVrx4W5U1Xfl2EB7Uu7+3NJvlJVDx7XTnpKkneswP0AAAAAsB2smerQ3TdW1fFJzkiyR5JXdvdFVXVykg3dvT7JK5K8rqo2Jrk6Q9CUJA9NcnJVfTPJTUl+tbuvHo89I8mrk9whybvHFwAAAAA7ockQKUm6+/Qkp8+1nTSzfV2SI5c5721J3raZa25Icv+tKRYAAACA1bG9F9YGAAAA4DZAiAQAAADAJCESAAAAAJOESAAAAABMEiIBAAAAMEmIBAAAAMAkIRIAAAAAk4RIAAAAAEwSIgEAAAAwSYgEAAAAwCQhEgAAAACThEgAAAAATBIiAQAAADBJiAQAAADAJCESAAAAAJOESAAAAABMEiIBAAAAMEmIBAAAAMAkIRIAAAAAk4RIAAAAAEwSIgEAAAAwSYgEAAAAwKQtYIaEAAAKhUlEQVSFQqSqOrSqLqmqjVV14jLH96qqN43Hz62q/cf2R1fVR6rqgvHnI2bOOXu85vnj654rdVMAAAAArKw1Ux2qao8kpyR5dJIrkpxXVeu7++KZbk9L8qXuvm9VHZXkRUmelOSLSX6mu/+9qu6f5Iwk+8ycd3R3b1ihewEAAABgO1lkJNIhSTZ296XdfUOS05IcPtfn8CSvGbffmuSRVVXd/bHu/vex/aIkd6iqvVaicAAAAAB2nEVCpH2SXD6zf0VuPproZn26+8Yk1yS5x1yfn0vy0e6+fqbtVeNUtudWVS335lV1XFVtqKoNmzZtWqBcAAAAAFbaDllYu6p+OMMUt1+ZaT66u38kyU+Or19c7tzuPrW713X3urVr127/YgEAAAC4hUVCpCuT7Dezv+/YtmyfqlqT5C5Jrhr3903y9iRP6e5PLZ3Q3VeOP69N8sYM0+YAAAAA2AktEiKdl+TAqjqgqvZMclSS9XN91ic5Ztw+IslZ3d1Vddck70pyYnf/81LnqlpTVXuP27dP8j+SXHjrbgUAAACA7WUyRBrXODo+w5PVPpHkzd19UVWdXFWHjd1ekeQeVbUxyQlJThzbj09y3yQnjWsfnV9V90yyV5IzqurjSc7PMJLp5St5YwAAAACsnDWLdOru05OcPtd20sz2dUmOXOa8FyZ54WYu+4DFywQAAABgNe2QhbUBAAAA2LUJkQAAAACYJEQCAAAAYJIQCQAAAIBJQiQAAAAAJgmRAAAAAJgkRAIAAABgkhAJAAAAgElCJAAAAAAmCZEAAAAAmCREAgAAAGCSEAkAAACASUIkAAAAACYJkQAAAACYJEQCAAAAYJIQCQAAAIBJQiQAAAAAJgmRAAAAAJgkRAIAAABgkhAJAAAAgElCJAAAAAAmCZEAAAAAmLRQiFRVh1bVJVW1sapOXOb4XlX1pvH4uVW1/8yxZ4/tl1TVYxe9JgAAAAA7j8kQqar2SHJKksclOSjJk6vqoLluT0vype6+b5KXJHnReO5BSY5K8sNJDk3yl1W1x4LXBAAAAGAnschIpEOSbOzuS7v7hiSnJTl8rs/hSV4zbr81ySOrqsb207r7+u7+dJKN4/UWuSYAAAAAO4k1C/TZJ8nlM/tXJHnQ5vp0941VdU2Se4zt58ydu8+4PXXNJElVHZfkuHH3q1V1yQI1A2yNvZN8cbWLYOdXL1rtCgDA31tY0AtqtStg13KfRTotEiKtqu4+Ncmpq10HcNtVVRu6e91q1wEAMMXfW4DVtMh0tiuT7Dezv+/YtmyfqlqT5C5JrtrCuYtcEwAAAICdxCIh0nlJDqyqA6pqzwwLZa+f67M+yTHj9hFJzuruHtuPGp/edkCSA5N8eMFrAgAAALCTmJzONq5xdHySM5LskeSV3X1RVZ2cZEN3r0/yiiSvq6qNSa7OEApl7PfmJBcnuTHJr3X3t5JkuWuu/O0BLMSUWQBgV+HvLcCqqWHAEAAAAABs3iLT2QAAAADYzQmRAAAAAJgkRAIAAABgkhAJAAAAgElCJGC3VVV3qKr7rXYdAABTqurOVfVdq10HsHsTIgG7par6mSTnJ3nPuH9wVa1f3aoAAG6uqh5YVRck+XiSC6vqX6vqAatdF7B7EiIBu6vnJzkkyZeTpLvPT3LAahYEALCMVyR5Rnfv3933SfJrSV61yjUBuykhErC7+mZ3XzPX1qtSCQDA5n2ru/9paae7P5jkxlWsB9iNrVntAgBWyUVV9fNJ9qiqA5P8RpIPrXJNAADz3l9VL0vytxn+g9eTkpxdVT+eJN390dUsDti9VLf/8A7sfqrqjkmek+QxSSrJGUl+v7uvW9XCAABmVNX7tnC4u/sRO6wYYLcnRAIAAABgkulswG6lqt6ZLax91N2H7cByAAC2qKrukeR5Sf5bhr/DfDDJyd191aoWBuyWjEQCditV9bAtHe/u9++oWgAAplTVmUk+kOT1Y9PRSR7e3Y9avaqA3ZUQCQAAYCdVVRd29/3n2i7o7h9ZrZqA3ZfpbMBupare3N1PrKoLcvNpbZVhccofXaXSAACW8w9VdVSSN4/7R2R4IAjADmckErBbqap7dffnquo+yx3v7s/s6JoAADanqq5Ncqck3xqb9kjytXG7u/vOq1IYsFsSIgG7rar6niSHZBiRdF53/8cqlwQAcAtVdfckByb5jqU26zgCq+F2q10AwGqoqqcn+XCSJ2QYFn5OVf3S6lYFAHBz499Z3p/kPUmeP/48aTVrAnZfRiIBu6WquiTJf116PO74+NwPdff9VrcyAIBvG9dxfGCSc7r74Kr6wSR/2N1PWOXSgN2QkUjA7uqqJNfO7F87tgEA7Eyu6+7rkqSq9uru/5vEf/QCVoWnswG7lao6YdzcmOTcqnpHhjWRDk/y8VUrDABgeVdU1V2T/H2SM6vqS0k8CARYFaazAbuVqnrelo539wt2VC0AAFujqh6W5C5J3tPdN6x2PcDuR4gE7Naq6juTpLu/utq1AAAA7MysiQTslqrq/lX1sSQXJbmoqj5SVT+82nUBAADsrIRIwO7q1CQndPd9uvs+SX4nyctXuSYAAICdlhAJ2F3dqbvft7TT3WcnudPqlQMAALBz83Q2YHd1aVU9N8nrxv1fSHLpKtYDAACwUzMSCdhd/VKStUneNr72TvLUVa0IAABgJyZEAnZX359kvwz/O7hnkkcm+cCqVgQAALATq+5e7RoAdriquiTJM5NcmOSmpfbu/syqFQUAALATsyYSsLva1N3vXO0iAAAAdhVGIgG7pap6ZJInJ3lvkuuX2rv771atKAAAgJ2YkUjA7uqpSX4wye3z7elsnUSIBAAAsAwjkYDdUlVd0t33W+06AAAAdhWezgbsrj5UVQetdhEAAAC7CiORgN1SVX0iyfcn+XSGNZEqSXf3j65qYQAAADspIRKwW6qq+yzX3t2f2dG1AAAA7AqESAAAAABMsiYSAAAAAJOESAAAAABMEiIBACyoqu5aVc9Y7ToAAFaDEAkAYHF3TSJEAgB2S0IkAIDF/XGS76+q86vqLVX1+KUDVfWGqjq8qo6tqndU1dlV9cmqet5Mn1+oqg+P57+sqvZYlbsAANgGQiQAgMWdmORT3X1wkr9IcmySVNVdkvzXJO8a+x2S5OeS/GiSI6tqXVX9UJInJXnIeP63khy9Y8sHANh2a1a7AACAXVF3v7+q/rKq1mYIjN7W3TdWVZKc2d1XJUlV/V2S/5bkxiQPSHLe2OcOSb6wKsUDAGwDIRIAwLZ7bZJfSHJUkqfOtPdcv05SSV7T3c/eQbUBAKwo09kAABZ3bZLvmtl/dZLfSpLuvnim/dFVdfequkOSxyf55yTvTXJEVd0zScbj99khVQMArAAjkQAAFtTdV1XVP1fVhUne3d3PqqpPJPn7ua4fTvK2JPsmeX13b0iSqvp/kvxDVd0uyTeT/FqSz+y4OwAA2HbVPT/aGgCARVTVHZNckOTHu/uase3YJOu6+/jVrA0AYKWZzgYAsA2q6lFJPpHkpUsBEgDAbZmRSAAAAABMMhIJAAAAgElCJAAAAAAmCZEAAAAAmCREAgAAAGCSEAkAAACASf8/MQjfYWO13voAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['type'] = df['site_id'].map(lambda x_: 'mobile' if x_ != '85f751fd' else 'app')\n",
    "gb = df.groupby('type')['click'].mean().sort_values(ascending=False)\n",
    "plot = gb.plot(kind='bar', title='Scores', figsize=(20, 5))\n",
    "plot.set_ylim(0, np.max(gb.values) + 0.02)\n",
    "plt.title('Mean CTR for app and mobile users', fontsize=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 中间结论\n",
    "app用户和mobile用户的平均CTR几乎相差2倍，换句话说意味着app用户和mobile用户在ctr中差别很大，考虑使用不同的处理方式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "dtype = {\n",
    "    'id': np.str, 'click': np.bool, 'hour': np.str,\n",
    "    'C1': np.uint16, 'banner_pos': np.uint16,\n",
    "    'site_id': np.str, 'site_domain': np.str, 'site_category': np.str,\n",
    "    'app_id': np.str, 'app_domain': np.str, 'app_category': np.str,\n",
    "    'device_id': np.str, 'device_ip': np.str, 'device_model': np.str, 'device_type': np.uint16,\n",
    "    'device_conn_type': np.uint16,\n",
    "    'C14': np.uint16, 'C15': np.uint16, 'C16': np.uint16, 'C17': np.uint16,\n",
    "    'C18': np.uint16, 'C19': np.uint16, 'C20': np.uint32, 'C21': np.uint16\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(train_data_path, dtype=dtype)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "17、统计点击和未点击的数量差异"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "click_ratio = df.groupby('click').click.count()\n",
    "click_ratio.plot(kind='bar', color=['#33FF9C', '#2980B9'])\n",
    "plt.ylabel(\"count\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "点击的数量和未点击的数量的比例为2:8，可以考虑使用下采样"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "18、统计各匿名特征中各种不同类别的点击和未点击的比例（包括'C1', 'C14', 'C15', 'C16', 'C17', 'C18', 'C19', 'C20', 'C21'）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x2880 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "anonymize_features = ['C1', 'C14', 'C15', 'C16', 'C17', 'C18', 'C19', 'C20', 'C21']\n",
    "\n",
    "fig, axes = plt.subplots(figsize=(17, 40), nrows=3, ncols=3)\n",
    "\n",
    "x = 0\n",
    "for row in np.arange(3):\n",
    "    for colum in np.arange(3):\n",
    "        count_df = df.groupby([anonymize_features[x], 'click']).click.count()\n",
    "        sum_df = df.groupby([anonymize_features[x]]).click.count()\n",
    "        ratio_df = (count_df / sum_df) * 100\n",
    "        ratio_df.unstack().plot(kind='barh', color=['#33FF9C', '#2980B9'], stacked=True, ax=axes[row, colum])\n",
    "        x = x + 1\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "匿名类别特征C14、C17、C20和C21具有大量的属性，因此可能对正标签具有更大的影响，需要重点关注"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "19、每天中每小时的点击次数和未点击次数统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['hour'] = df['hour'].apply(lambda x_: pd.datetime.strptime(x_, '%y%m%d%H'))\n",
    "df['hour_of_day'] = df['hour'].apply(lambda x_: x_.hour)\n",
    "\n",
    "fig, ax0 = plt.subplots(figsize=(10, 7))\n",
    "ax1 = ax0.twinx()\n",
    "\n",
    "hourday_df = df.groupby(['hour_of_day', 'click']).size()\n",
    "hourday_df.unstack().plot(kind='bar', stacked=True, color=['#33FF9C', '#2980B9'], title=\"Hour of the day\", ax=ax0)\n",
    "\n",
    "click_by_hour = (df[df.click == 1].groupby(['hour_of_day']).size() / df.groupby(['hour_of_day']).size()) * 100\n",
    "\n",
    "click_by_hour.plot(kind='line', ylim=(0, 100), ax=ax1, color='#FACC37')\n",
    "\n",
    "ax0.set_ylabel(\"Count\")\n",
    "ax1.set_ylabel(\"Percentage of Click\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "统计的目的是了解点击率是否在一天中的任何特定时间增加。\n",
    "点击率保持在16%-18%的范围内，表明点击率的分布在一天中是相似的。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "20、对“id”和“device_ip”进行统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>40428967.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            count\n",
       "count  40428967.0\n",
       "mean          1.0\n",
       "std           0.0\n",
       "min           1.0\n",
       "25%           1.0\n",
       "50%           1.0\n",
       "75%           1.0\n",
       "max           1.0"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['id', 'device_ip']].groupby(['id', 'device_ip']).device_ip.count().reset_index(name=\"count\").describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, axes = plt.subplots(figsize=(15, 7), nrows=1, ncols=2)\n",
    "\n",
    "device_type = df.groupby(['device_type', 'click']).size()\n",
    "device_type.unstack().plot(kind='bar', stacked=True, color=['#33FF9C', '#2980B9'], title='Device Type', ax=axes[0])\n",
    "\n",
    "device_conn = df.groupby(['device_conn_type', 'click']).size()\n",
    "device_conn.unstack().plot(kind='bar', stacked=True, color=['#33FF9C', '#2980B9'], title='Device Connection Type',\n",
    "                           ax=axes[1])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "设备IP是唯一的，对于设备类型和设备连接类型来说，其标准差为零，不太频繁的属性似乎不能很好的反映正标签"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "21、对Banner Position（广告位置）进行统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, axes = plt.subplots(figsize=(15, 7), nrows=1, ncols=2)\n",
    "\n",
    "banner_pos = df.groupby(['banner_pos', 'click']).size()\n",
    "banner_pos.unstack().plot(kind='bar', stacked=True, color=['#33FF9C', '#2980B9'], title='Banner Position', ax=axes[0])\n",
    "\n",
    "banner_pos_zoom = banner_pos.iloc[4:]\n",
    "banner_pos_zoom.unstack().plot(kind='bar', stacked=True, color=['#33FF9C', '#2980B9'],\n",
    "                               title='Banner Position except 0 and 1', ax=axes[1])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "位置在0和1是最常见的。位置7能够更好的反映正标签。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "22、对与site和app相关的特征进行分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>app_id</th>\n",
       "      <th>app_domain</th>\n",
       "      <th>app_category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>40428967</td>\n",
       "      <td>40428967</td>\n",
       "      <td>40428967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>8552</td>\n",
       "      <td>559</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>ecad2386</td>\n",
       "      <td>7801e8d9</td>\n",
       "      <td>07d7df22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>25832830</td>\n",
       "      <td>27237087</td>\n",
       "      <td>26165592</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          app_id app_domain app_category\n",
       "count   40428967   40428967     40428967\n",
       "unique      8552        559           36\n",
       "top     ecad2386   7801e8d9     07d7df22\n",
       "freq    25832830   27237087     26165592"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['app_id', 'app_domain', 'app_category']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>site_id</th>\n",
       "      <th>site_domain</th>\n",
       "      <th>site_category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>40428967</td>\n",
       "      <td>40428967</td>\n",
       "      <td>40428967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>4737</td>\n",
       "      <td>7745</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>85f751fd</td>\n",
       "      <td>c4e18dd6</td>\n",
       "      <td>50e219e0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>14596137</td>\n",
       "      <td>15131739</td>\n",
       "      <td>16537234</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         site_id site_domain site_category\n",
       "count   40428967    40428967      40428967\n",
       "unique      4737        7745            26\n",
       "top     85f751fd    c4e18dd6      50e219e0\n",
       "freq    14596137    15131739      16537234"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['site_id', 'site_domain', 'site_category']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n"
     ]
    }
   ],
   "source": [
    "print(df[(df.app_id == 'ecad2386') & (df.site_id == '85f751fd')].id.count())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "site和app的ID是互补的。把这些特征合并在一起可以节省空间，且两者不可能同时出现"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2、特征结果联合分布"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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GICKmAFuBG8ZzzP+54LVtqOwlh6x/qKn91qxZw7p161i9uprPAUjSeHVySuc3gO9m5g862GbbvPGNb2TWrFlVlyFJY9bJT9quAq4c/mRErAXWAsw7aGoHy5GkeunICD8ipgErgGuGb8vMDZnZl5l9s2ZM6UQ5klRLnZrS+W3g/sz83w61J0kaplOBfzojTOdIkjqn9MCPiBnAbwLXl91WmU4//XSWLVvGli1b6Onp4ZJLLqm6JElqSelv2mbm/wEHt+t4zV5G2W5XXukfKJImNj9pK0k1YeBLUk0Y+JJUExMi8DOz6hJGNRFqlFRvXR/406dPZ3BwsKsDNTMZHBxk+vTpVZciSXvV9V9i3tPTw8DAAE8++WTVpezT9OnT6enpqboMSdqrrg/8qVOnsmDBgqrLkKQJr6umdKbNXVx1CZI0aXVV4EuSymPgS1JNRDdd/RIR24EtVdfRBWYDT1VdRBewH+yD3eyHfffBoZk5Z7QDdNubtlsys6/qIqoWEf32g/0A9sFu9kN7+sApHUmqCQNfkmqi2wJ/Q9UFdAn7ocF+sA92sx/a0Add9aatJKk83TbClySVpJLAj4hTImJLRDwaEX82wvYDIuLqYvs9EdHb+SrL10Q/rImIJyPigeL2x1XUWaaI+HRE/CgivrWX7RERFxd99M2IeF2nayxbE33w5oj46ZDzYH2nayxbRMyPiDsi4uGI2BQR546wTx3OhWb6YeznQ2Z29AZMAb4LHAZMAx4Ejhy2z3uBTxX3VwFXd7rOLumHNcAnq6615H54I/A64Ft72X4q8EUggBOAe6quuYI+eDPwharrLLkP5gKvK+7PBB4Z4d9DHc6FZvphzOdDFSP844FHM/OxzNwBXAW8bdg+bwMuK+5fC/xGREQHa+yEZvph0svMu4Bt+9jlbcDl2fDfwC9FxNzOVNcZTfTBpJeZT2Tm/cX97cBmYN6w3epwLjTTD2NWReDPAx4f8niAX/yFXtwnM3cCP6WNX4TeJZrpB4DfL/58vTYi5nemtK7SbD9Ndssi4sGI+GJETOpVBosp3GOBe4ZtqtW5sI9+gDGeD75p290+D/Rm5tHAbbz0V4/q5X4aH51fAvw98B8V11OaiHg5cB1wXmY+XXU9VRmlH8Z8PlQR+FuBoSPVnuK5EfeJiP2Bg4DBjlTXOaP2Q2YOZubPi4f/ChzXodq6STPny6SWmU9n5s+K+zcDUyNidsVltV1ETKURcldk5vUj7FKLc2G0fhjP+VBF4N8HvDoiFkTENBpvyt44bJ8bgXcV998O3J7FuxWTyKj9MGx+cgWN+by6uRFYXVyhcQLw08x8ouqiOikifmX3e1gRcTyNf7eTagBU/H6XAJsz86K97Dbpz4Vm+mE850PHF0/LzJ0RsQ74TxpXqnw6MzdFxAVAf2beSOMX/mxEPErjzaxVna6zbE32wzkRsQLYSaMf1lRWcEki4koaVx3MjogB4MPAVIDM/BRwM42rMx4FngH+qJpKy9NEH7wdeE9E7ASeBVZNwgHQScAZwEMR8UDx3F8Ah0B9zgWa64cxnw9+0laSasI3bSWpJgx8SaoJA1+SasLAl6SaMPAlqUKjLZ43bN+/HbJo2iMR8ZNW2jLwpTaLiPMi4mVV16EJ41LglGZ2zMw/ycxjMvMYGp+yHekDantl4Evtdx5g4KspIy2eFxELI+KWiNgYEV+JiCNGeOnpwJWttGXgq5YiYnWxKN2DEfHZiOiNiNuL5/4rIg4p9rs0It4+5HU/K36+OSLuLBa1+3ZEXFF8AvQc4FeBOyLijmp+O00CG4CzM/M44E+Bfxy6MSIOBRYAt7dy0I5/0laqWrG64F8CJ2bmUxExi8bCdJdl5mURcSZwMfC7oxzqWGAx8EPga8BJmXlxRLwPODkznyrvt9BkVSycdiJwzZBV4Q8Yttsq4NrM3NXKsQ181dFy4JrdgZyZ2yJiGfB7xfbPAh9v4jj3ZuYAQPEx+F7gq+0vVzWzH/CTYp5+b1YBZ43lwJL2bifFv5OI2I/Gt5Pt9vMh93fhAEptUCyH/L2IWAkvfrXjkt3bi/n8VwJfb/XYBr7q6HZgZUQcDFBM6dzNS4v0vQP4SnH/+7y0LPUKikXNRrGdxtfTSaMqFs/7OrAoIgYi4t00zsF3R8SDwCb2/Da8VcBVY1lAzxGJaqdYlfSvgS9HxC7gG8DZwGci4gPAk7y0EuO/AJ8r/uHdAvxfE01sAG6JiB9m5snt/w00mWTm6XvZNOKlmpl5/ljbcrVMSaoJp3QkqSYMfEmqCQNfkmrCwJekmjDwJakmDHxJqgkDX5JqwsCXpJr4f5ClehedG9JjAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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uuvBbJb3Q434le6zPfSJiv6T/lTS2kHR9qyVzT5epepZUpkEzZ3+uj4+I+4oM1o9afsZnSDrD9vdsb7I9p7B0fasl87WSPmK7ouqZ3LJioh2xoT7XG00j/O4NynarpA9I+peix260d9oe02x/RFKHpPPLzjIQ22+SdIOkxSVHGYrhqk7rvEfVs7iHbL8jIn5ZaqqBLZS0KiL+yfYsSV+xPT0iXis72PHG9gWqFv7vlp2lBp+X9JcR8VrRkxdFF/4OSeN73G/LHutrn4rt4ar+KdxdTLw+1ZJZti+SdI2k8yPiNwVl689gmUdLmi7p29kT7m2S7rE9LyLK+MixWn7GFVXnZ1+V9LztZ1X9B2BzMREPU0vmyyTNkaSIeNR2s6prqZQ9HdWfmp7rjcb22ZL+VdLFEVFmV9SqQ9Ka7HevRdJc2/sj4j9yH7ngixnDJf1E0kS9caFrWq99LtehF22/WmTGI8w8U9ULeG8vM+tQMvfa/9sq96JtLT/jOZJuzW63qDr1MLbBMz8gaXF2+yxV5/Bd8nOjXf1fAP1DHXrR9vEys9aYeYKk5ySdV3bOWjP32m+VCrxoW+gZfkTst32FpK+repX6lojYavs6SV0RcY+km1X90/c5VS98LCgyY281Zl4haZSkO7J/tX8WEfMaPHPDqDHv1yX9ge1nJB2QdHWUeDZXY+ZPS/qy7U+qegF3cWS/5WWwfbuqU2It2XWFv5HUJEkR8SVVrzPMVbVAfyXpo+UkfUMNmZereo3vi9nv3v4oeUG1GjKXhnfaAkAieKctACSCwgeARFD4AJAICh8AEkHhA0BJal1oLdv3c7afyL6etT3kNx1S+EAd2b7S9lvKzoFjxiplb84bTER8MiLeGRHvlPTPkr421MEofKC+rpRE4aMm0cdCa7Yn2V5ve4vt79o+s4//daGk24c6HoWP5NhelK2h/qTtr9hut72hx+cZTMj2W9VzrXLbr2T/fY/tb9u+0/aPbN+WrSX/CUm/LWmj7Y3lfHc4DqyUtCwizpF0laQv9tzo6udtTFR1eeUhYfE0JMX2NEl/repb8XfaHqPqcty3RsSttpdIulHS+wc51ExJ01RdLuF7kt4dETfa/pSkCyJiZ37fBY5Xtkepusb/6+/al6Q399ptgaQ7I+LAUI9P4SM1F0q64/VCjohd2UqWf5Rt/4qkf6zhOI9HREWSbD+h6topD9c/LhLzJkm/zObp+7NA1TXHjujgAPq2X9nvSLak9Ige23quiHpAnDyhDiJit6qrwc6XDn7s5MGPbczm80+R9OiRHJ/CR2o2SJpve6wkZVM6j+iNRfo+LOm72e2fSjonuz1P2QJYg9ij6vLTwKCyhdYelTTFdsX2Zao+By+z/aSkrTr0k9QWSFpzpIvwcVaCpGQrWv69pO/YPqDq5+Quk/Rvtq+W9LLeWCXyy5Luzn7x1kv6vxqGWClpve2fR8QF9f8OcDyJiIX9bOrzpZoRce3RjMdqmQCQCKZ0ACARFD4AJILCB4BEUPgAkAgKHwASQeEDQCIofABIBIUPAIn4f4ZxHOLYqD1bAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "var=[ 'hour', 'C1', 'banner_pos', 'site_category',  'app_domain', 'app_category', \n",
    "        'device_type', 'device_conn_type', 'C15', 'C16', 'C17', 'C18', 'C19', 'C20', 'C21']\n",
    "for v in var:\n",
    "    #按多少的顺序排列的特征的列表\n",
    "    sns.countplot(y=v,hue='click',hue_order=[0,1],data=df)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3、重点关注特征"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 取概率提升比达到30%的特征，即概率提升5%的特征作为重点关注的特征，为避免样本没有代表性，要求该特征的样本数大于10，其它特征也有一定作用（比如hour），但作用可能没这么明显，对重点特征可在特征工程时候着重考虑。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "hour属性的取值和次数\n",
      "Empty DataFrame\n",
      "Columns: [特征分布, P_C, P_C|A, P_A|C, 概率提升比%]\n",
      "Index: []\n",
      "\n",
      "C1属性的取值和次数\n",
      "Empty DataFrame\n",
      "Columns: [特征分布, P_C, P_C|A, P_A|C, 概率提升比%]\n",
      "Index: []\n",
      "\n",
      "banner_pos属性的取值和次数\n",
      "    特征分布       P_C     P_C|A   P_A|C     概率提升比%\n",
      "7  43577  0.001078  0.002032  0.3201  88.509688\n",
      "\n",
      "site_category属性的取值和次数\n",
      "             特征分布       P_C     P_C|A     P_A|C      概率提升比%\n",
      "dedf689d    24500  0.000606  0.001834  0.514000  202.699042\n",
      "3e814130  3050306  0.075449  0.125745  0.283003   66.662768\n",
      "42a36e14     2515  0.000062  0.000085  0.231014   36.046092\n",
      "\n",
      "app_domain属性的取值和次数\n",
      "            特征分布           P_C         P_C|A     P_A|C      概率提升比%\n",
      "5576cc84      21  5.194295e-07  2.476305e-06  0.809524  376.735568\n",
      "999f1fac      33  8.162464e-07  3.204631e-06  0.666667  292.605762\n",
      "99b4c806   10041  2.483615e-04  9.372088e-04  0.640773  277.356658\n",
      "391ef1c3      11  2.720821e-07  1.019655e-06  0.636364  274.760045\n",
      "73fc6786     105  2.597148e-06  9.613892e-06  0.628571  270.171147\n",
      "eaaf6d12      53  1.310941e-06  4.806946e-06  0.622642  266.678966\n",
      "f5a7c834     166  4.105967e-06  1.500350e-05  0.620482  265.407170\n",
      "a5ab1a9f      15  3.710211e-07  1.310985e-06  0.600000  253.345186\n",
      "e4a3128e      11  2.720821e-07  8.739901e-07  0.545455  221.222896\n",
      "800100e0      32  7.915117e-07  2.476305e-06  0.531250  212.857716\n",
      "44324ff4      31  7.667769e-07  2.330640e-06  0.516129  203.952848\n",
      "6437e20c      31  7.667769e-07  2.330640e-06  0.516129  203.952848\n",
      "5bcedd7d     125  3.091843e-06  8.739901e-06  0.480000  182.676148\n",
      "1c895c8c      18  4.452253e-07  1.165320e-06  0.444444  161.737175\n",
      "1ddc989f      46  1.137798e-06  2.621970e-06  0.391304  130.442512\n",
      "b97def0d     133  3.289720e-06  7.574581e-06  0.390977  130.249996\n",
      "e25ea824      13  3.215516e-07  7.283251e-07  0.384615  126.503324\n",
      "b3c288b7      16  3.957558e-07  8.739901e-07  0.375000  120.840741\n",
      "c41aa5ee      11  2.720821e-07  5.826601e-07  0.363636  114.148597\n",
      "bb2a164d      17  4.204906e-07  8.739901e-07  0.352941  107.850109\n",
      "23e2c80e      48  1.187268e-06  2.330640e-06  0.333333   96.302881\n",
      "af237497      15  3.710211e-07  7.283251e-07  0.333333   96.302881\n",
      "9cc1123d      22  5.441643e-07  1.019655e-06  0.318182   87.380023\n",
      "c72257c6      20  4.946948e-07  8.739901e-07  0.300000   76.672593\n",
      "6b062297      11  2.720821e-07  4.369951e-07  0.272727   60.611448\n",
      "316edd1b      11  2.720821e-07  4.369951e-07  0.272727   60.611448\n",
      "9830a8fb      31  7.667769e-07  1.165320e-06  0.258065   51.976424\n",
      "d3e7c965      16  3.957558e-07  5.826601e-07  0.250000   47.227161\n",
      "b8d325c3  534000  1.320835e-02  1.807310e-02  0.232346   36.830828\n",
      "6f7ca2ba  226100  5.592525e-03  7.467226e-03  0.226727   33.521556\n",
      "6bfb9168      27  6.678380e-07  8.739901e-07  0.222222   30.868587\n",
      "9d65dcb9      36  8.904507e-07  1.165320e-06  0.222222   30.868587\n",
      "\n",
      "app_category属性的取值和次数\n",
      "             特征分布       P_C     P_C|A     P_A|C     概率提升比%\n",
      "8df2e842     1679  0.000042  0.000064  0.259678  52.926842\n",
      "f95efa07  1141673  0.028239  0.041174  0.247588  45.806437\n",
      "\n",
      "device_type属性的取值和次数\n",
      "Empty DataFrame\n",
      "Columns: [特征分布, P_C, P_C|A, P_A|C, 概率提升比%]\n",
      "Index: []\n",
      "\n",
      "device_conn_type属性的取值和次数\n",
      "Empty DataFrame\n",
      "Columns: [特征分布, P_C, P_C|A, P_A|C, 概率提升比%]\n",
      "Index: []\n",
      "\n",
      "C15属性的取值和次数\n",
      "         特征分布       P_C     P_C|A     P_A|C      概率提升比%\n",
      "768      1621  0.000040  0.000101  0.425663  150.676720\n",
      "300   2337294  0.057812  0.122348  0.359358  111.628957\n",
      "480      2137  0.000053  0.000083  0.267665   57.630203\n",
      "1024     2560  0.000063  0.000095  0.254688   49.987670\n",
      "\n",
      "C16属性的取值和次数\n",
      "         特征分布       P_C     P_C|A     P_A|C      概率提升比%\n",
      "1024     1621  0.000040  0.000101  0.425663  150.676720\n",
      "250   1806334  0.044679  0.110865  0.421347  148.134756\n",
      "320      2137  0.000053  0.000083  0.267665   57.630203\n",
      "768      2560  0.000063  0.000095  0.254688   49.987670\n",
      "\n",
      "C17属性的取值和次数\n",
      "        特征分布       P_C     P_C|A     P_A|C      概率提升比%\n",
      "2518    3100  0.000077  0.000326  0.721290  324.774105\n",
      "2662    1747  0.000043  0.000172  0.677733  299.122972\n",
      "1694    6759  0.000167  0.000622  0.632046  272.217447\n",
      "2286   68257  0.001688  0.005813  0.584614  244.284256\n",
      "2295  209715  0.005187  0.017471  0.571933  236.816486\n",
      "2569   28066  0.000694  0.002250  0.550381  224.124271\n",
      "827    17588  0.000435  0.001345  0.524846  209.086632\n",
      "2162  267569  0.006618  0.019510  0.500574  194.792169\n",
      "2331  238225  0.005892  0.016721  0.481847  183.763859\n",
      "2284    9763  0.000241  0.000659  0.463075  172.708796\n",
      "1994  604968  0.014964  0.034961  0.396727  133.635823\n",
      "2016    5042  0.000125  0.000286  0.389330  129.279585\n",
      "1272   13311  0.000329  0.000732  0.377357  122.228842\n",
      "2443   70802  0.001751  0.003845  0.372828  119.561897\n",
      "2719      94  0.000002  0.000005  0.372340  119.274495\n",
      "1903    2094  0.000052  0.000110  0.361509  112.895818\n",
      "2663    4110  0.000102  0.000216  0.361071  112.637573\n",
      "1993  495667  0.012260  0.026013  0.360280  112.172117\n",
      "2512  175427  0.004339  0.008556  0.334812   97.173463\n",
      "2285    5227  0.000129  0.000250  0.328487   93.448659\n",
      "2594    1629  0.000040  0.000076  0.321670   89.434088\n",
      "2253  162976  0.004031  0.007589  0.319679   88.261709\n",
      "2635    2058  0.000051  0.000095  0.318270   87.432051\n",
      "1939    7501  0.000186  0.000340  0.311425   83.400958\n",
      "2510    1009  0.000025  0.000046  0.310208   82.684247\n",
      "1926   34893  0.000863  0.001569  0.308601   81.737548\n",
      "1872  695237  0.017197  0.030478  0.300953   77.234110\n",
      "1447   55747  0.001379  0.002442  0.300698   77.083531\n",
      "2717  148987  0.003685  0.006509  0.299925   76.628717\n",
      "1991   28168  0.000697  0.001223  0.298140   75.577066\n",
      "...      ...       ...       ...       ...         ...\n",
      "2471    6875  0.000170  0.000242  0.241600   42.280328\n",
      "2421    4448  0.000110  0.000156  0.240782   41.798821\n",
      "572   294504  0.007284  0.010309  0.240306   41.518124\n",
      "2672   31564  0.000781  0.001104  0.240179   41.443303\n",
      "2225   38348  0.000949  0.001341  0.240117   41.406873\n",
      "1921   89617  0.002217  0.003126  0.239463   41.022122\n",
      "2533   19076  0.000472  0.000665  0.239254   40.898461\n",
      "2551    3958  0.000098  0.000138  0.239010   40.754820\n",
      "2303   37202  0.000920  0.001290  0.238025   40.174884\n",
      "2500   73637  0.001821  0.002549  0.237639   39.947477\n",
      "2712   12945  0.000320  0.000447  0.237312   39.754913\n",
      "2735    3685  0.000091  0.000127  0.236635   39.356401\n",
      "2702     835  0.000021  0.000029  0.234731   38.234843\n",
      "2642    6450  0.000160  0.000220  0.234574   38.142446\n",
      "2060  262230  0.006486  0.008945  0.234176   37.908332\n",
      "2711    6821  0.000169  0.000233  0.234130   37.881117\n",
      "1515     120  0.000003  0.000004  0.233333   37.412017\n",
      "2508    3168  0.000078  0.000107  0.232639   37.003052\n",
      "2667  356378  0.008815  0.012029  0.231712   36.457102\n",
      "2716  274951  0.006801  0.009244  0.230805   35.922919\n",
      "2550  102083  0.002525  0.003415  0.229627   35.229250\n",
      "2467  132686  0.003282  0.004435  0.229459   35.130402\n",
      "2655   42296  0.001046  0.001407  0.228343   34.473228\n",
      "1780   94378  0.002334  0.003122  0.227129   33.758351\n",
      "479   199002  0.004922  0.006536  0.225475   32.784247\n",
      "2605     289  0.000007  0.000009  0.224913   32.453501\n",
      "2545  713546  0.017649  0.023355  0.224702   32.328774\n",
      "2439    7840  0.000194  0.000256  0.223980   31.903517\n",
      "2646   22931  0.000567  0.000747  0.223715   31.747474\n",
      "2624  194761  0.004817  0.006290  0.221697   30.559493\n",
      "\n",
      "[92 rows x 5 columns]\n",
      "\n",
      "C18属性的取值和次数\n",
      "      特征分布       P_C    P_C|A     P_A|C     概率提升比%\n",
      "2  7116058  0.176014  0.30576  0.294976  73.713806\n",
      "\n",
      "C19属性的取值和次数\n",
      "         特征分布       P_C     P_C|A     P_A|C      概率提升比%\n",
      "1071    21210  0.000525  0.001465  0.474116  179.211000\n",
      "1063   522944  0.012935  0.027085  0.355562  109.393518\n",
      "1447      161  0.000004  0.000008  0.347826  104.837789\n",
      "303    328180  0.008117  0.014982  0.313410   84.570048\n",
      "939      5421  0.000134  0.000231  0.292750   72.403250\n",
      "431    430005  0.010636  0.015437  0.246458   45.141010\n",
      "39    8829426  0.218394  0.314028  0.244163   43.789758\n",
      "1327  1092601  0.027025  0.036912  0.231927   36.583991\n",
      "1319   394524  0.009758  0.013168  0.229142   34.943677\n",
      "1711    94378  0.002334  0.003122  0.227129   33.758351\n",
      "\n",
      "C20属性的取值和次数\n",
      "           特征分布       P_C     P_C|A     P_A|C     概率提升比%\n",
      "100100       79  0.000002  0.000004  0.316456  86.363495\n",
      "100073     2040  0.000050  0.000091  0.306373  80.425442\n",
      "100173   102213  0.002528  0.004009  0.269291  58.587561\n",
      "100071     3334  0.000082  0.000131  0.268746  58.266990\n",
      "100175      196  0.000005  0.000008  0.265306  56.241068\n",
      "100206     2252  0.000056  0.000087  0.264654  55.856817\n",
      "100049    11985  0.000296  0.000450  0.257906  51.882905\n",
      "100224     2042  0.000051  0.000076  0.256121  50.832135\n",
      "100101    57975  0.001434  0.002081  0.246468  45.147315\n",
      "100070    10746  0.000266  0.000375  0.239345  40.952264\n",
      "100137      507  0.000013  0.000017  0.236686  39.386661\n",
      "100068    14340  0.000355  0.000494  0.236471  39.260056\n",
      "100148  1794890  0.044396  0.060929  0.233039  37.238560\n",
      "100078       43  0.000001  0.000001  0.232558  36.955498\n",
      "100213      768  0.000019  0.000026  0.229167  34.958231\n",
      "100221    75865  0.001877  0.002500  0.226231  33.229276\n",
      "100004    84961  0.002101  0.002792  0.225586  32.849461\n",
      "\n",
      "C21属性的取值和次数\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       特征分布       P_C     P_C|A     P_A|C      概率提升比%\n",
      "33  1497559  0.037042  0.085930  0.393919  131.982326\n",
      "35    46707  0.001155  0.001935  0.284454   67.517508\n",
      "52  1203050  0.029757  0.047446  0.270743   59.442713\n",
      "82    71393  0.001766  0.002767  0.266091   56.703003\n",
      "16   347178  0.008587  0.013123  0.259501   52.822317\n",
      "32  1783343  0.044111  0.059836  0.230343   35.651123\n"
     ]
    }
   ],
   "source": [
    "for v in var:\n",
    "    print('\\n%s属性的取值和次数'%v)\n",
    "    P=pd.concat([df[v].value_counts(),df[v].value_counts(normalize=True),\\\n",
    "                   train_df_click[v].value_counts(normalize=True)],\\\n",
    "                   axis=1,join_axes=[df[v].value_counts().index],keys=['特征分布','P_C','P_C|A']).fillna(0)\n",
    "    #P(A│ci)=(P(ci│A)P(A))/(P(ci))\n",
    "    P['P_A|C']=(P['P_C|A']*P_A)/P['P_C']\n",
    "    P['概率提升比%']=(P['P_A|C']-P_A)*100/P_A\n",
    "    P=P[(P['概率提升比%']>30)&(P['特征分布']>10)]\n",
    "    print(P.sort_values(by='概率提升比%',ascending=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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